
#import dependencies
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sb
import helpers
import matplotlib.dates as mdates
import plotly.express as px
import plotly.graph_objects as go
import re
import warnings
warnings.filterwarnings('ignore')
sb.set_style("darkgrid")
%matplotlib inline


# load data
df = pd.read_csv("cleaned_data/reddit_cleaned_2019.csv")
df_merged = pd.read_csv("cleaned_data/reddit_merged_2019.csv")

df_users = pd.read_csv("cleaned_data/users_cleaned.csv")


# convert to datetime
df.created_at = pd.to_datetime(df.created_at)
df_merged.created_at = pd.to_datetime(df_merged.created_at)
df_merged.user_created_at = pd.to_datetime(df_merged.user_created_at)
df_users.user_created_at = pd.to_datetime(df_users.user_created_at)


px.bar(data_frame=df['submission_comment'].value_counts().to_frame().reset_index(),
       x="index", y="submission_comment", color='submission_comment', text = 'submission_comment' ).update_layout(title='Comment or Submission',
                   xaxis_title='contribution category',
                   yaxis_title='number of contributions').update_traces(marker_color='#5296dd')


fig = px.pie(data_frame=df['submission_comment'].value_counts().to_frame().reset_index(), values='submission_comment', names='index',
             title='Comment or Submission')
fig.show()


df.author.value_counts().to_frame().head(10).reset_index()


fig = px.bar(df.author.value_counts().to_frame().head(10).reset_index(), x="author", y="index",
             height=500,
             title='Most commented user in 2019').update_traces(marker_color='#5296dd',).update_layout(
                   xaxis_title='number of comments',
                   yaxis_title='user name').update_traces(marker_color='#5296dd')

fig.update_yaxes(autorange="reversed")


df.author.value_counts().to_frame().head(10).reset_index()


df_auto_moderator = df.query(" author == 'AutoModerator' ").reset_index(drop=True)
print(df_auto_moderator.shape)
df_auto_moderator.head(1)

(426, 17)


df_auto_moderator.submission_comment.value_counts()

comment    426
Name: submission_comment, dtype: int64


df_auto_moderator.subreddit.value_counts().head(10)

r/JerkOffToCelebs     189
r/Celebhub            102
r/TrueFMK              21
r/OutOfTheLoop         20
r/CelebEconomy         16
r/DC_Cinematic         12
r/SexiestLeague         5
r/AskReddit             5
r/celebnsfw             4
r/unpopularopinion      4
Name: subreddit, dtype: int64


df_auto_moderator['permalink'].iloc[26]

'/r/Celebhub/comments/arpqrd/amber_heard/egosb56/'


df_auto_moderator.text.value_counts().head()

**Thank you for your submission. Make sure to follow the rules.**\n\n**Don't forget to follow us on [Instagram](https://www.instagram.com/jotocelebs/) and [join our Discord Server](https://discord.gg/PrRFWsa)!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/JerkOffToCelebs) if you have any questions or concerns.*                                                                          64
Remember to keep comments civil.\n\n**[Follow our Instagram page](https://www.instagram.com/celebtag/) for more celebrity content and daily top posts!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/Celebhub) if you have any questions or concerns.*                                                                                                                                            59
**Thank you for your submission. Make sure to follow the rules.**\n\n**Check out our [FAP LOTTERY!](https://jerkofftocelebs.com/)**\n\n**Don't forget to follow us on [Instagram](https://www.instagram.com/jotocelebs/) and [join our Discord Server](https://discord.gg/PrRFWsa)!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/JerkOffToCelebs) if you have any questions or concerns.*        54
**Thank you for your submission. Make sure to follow the rules.**\n\n**Check out our [NEW FAP LOTTERY!](https://jerkofftocelebs.com/)**\n\n**Don't forget to follow us on [Instagram](https://www.instagram.com/jotocelebs/) and [join our Discord Server](https://discord.gg/PrRFWsa)!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/JerkOffToCelebs) if you have any questions or concerns.*    40
Make sure to follow our community guidelines.\n\n**[Get user flair](https://redd.it/e0a4mn) and [check out our Instagram page](https://www.instagram.com/celebtag/) for more celebrity content!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/Celebhub) if you have any questions or concerns.*                                                                                                   17
Name: text, dtype: int64


df_vote_bot = df.query(" author == 'CelebBattleVoteBot' ").reset_index(drop=True)
print(df_vote_bot.shape)
df_vote_bot.head()

(120, 17)


df_vote_bot['permalink'].iloc[0]

'/r/CelebBattles/comments/ba5rm3/amber_heard_vs_scarlett_johansson/ek959vk/'


df_vote_bot.subreddit.value_counts().head(10)

r/CelebBattles    116
r/Celebhub          4
Name: subreddit, dtype: int64


df_vote_bot.submission_comment.value_counts()

comment    120
Name: submission_comment, dtype: int64


df_vote_bot.created_at.dt.date.value_counts()

2019-04-19    4
2019-12-19    4
2019-10-08    3
2019-08-07    3
2019-05-19    2
             ..
2019-06-30    1
2019-04-28    1
2019-06-18    1
2019-12-26    1
2019-05-09    1
Name: created_at, Length: 96, dtype: int64


df_vote_bot.text.value_counts().head()

Winner of this battle: Amber Heard\n\nTotal votes cast: 219\n\nAmber Heard: 113\n\nGal Gadot: 106\n\nAmber Heard won this battle by a margin of 7 votes\n\nPie chart: https://i.imgur.com/py1Bwdl.png\n\n---\n\n^^Results ^^are ^^considered ^^decisive ^^after ^^120 ^^hours ^^of ^^battle ^^start. ^^I'm ^^a ^^bot. ^^This ^^action ^^was ^^performed ^^automatically.    1
Vote here: https://youpoll.me/25712/\n\nResults: https://youpoll.me/25712/r\n\n---\n\n^^I'm ^^a ^^bot. ^^This ^^action ^^was ^^performed ^^automatically.                                                                                                                                                                                                                   1
Vote here: https://youpoll.me/26795/\n\nResults: https://youpoll.me/26795/r\n\n---\n\n^^I'm ^^a ^^bot. ^^This ^^action ^^was ^^performed ^^automatically.                                                                                                                                                                                                                   1
Vote here: https://youpoll.me/15158/\n\nResults: https://youpoll.me/15158/r\n\n---\n\n^^I'm ^^a ^^bot. ^^This ^^action ^^was ^^performed ^^automatically.                                                                                                                                                                                                                   1
Vote here: https://youpoll.me/15572/\n\nResults: https://youpoll.me/15572/r\n\n---\n\n^^I'm ^^a ^^bot. ^^This ^^action ^^was ^^performed ^^automatically.                                                                                                                                                                                                                   1
Name: text, dtype: int64


df_spells = df.query(" author == 'spells010' ").reset_index(drop=True)
print(df_spells.shape)
df_spells.head()

(80, 17)


df_spells.submission_comment.value_counts()

submission    80
Name: submission_comment, dtype: int64


df_spells['permalink'].iloc[0]

'/r/u_spells010/comments/ckz6p7/how_can_i_meet_amber_heard_91_9116496706_clontact/'


df_spells.subreddit.value_counts().head(10)

u/spells010    80
Name: subreddit, dtype: int64


df_spells.text.value_counts().head(10)

Amber Heard Make Him Love Me by love spell (clontact phone / mobile number +91 9116496706 whatsapp)         5
powerful attraction love spell for Amber Heard ( +91 9116496706 clontact phone / mobile number whatsapp)    5
how to become Amber Heard 's' wife ( +91 9116496706 clontact phone / mobile number whatsapp)                4
how to make love marrige with Amber Heard ( +91 9116496706 clontact phone / mobile number whatsapp)         4
how to become boyfriend Amber Heard ( +91 9116496706 clontact phone / mobile number whatsapp)               4
Joining Together love Photo Spell Amber Heard ( +91 9116496706 clontact phone / mobile number whatsapp)     4
how to make fall in love Amber Heard ( +91 9116496706 clontact phone / mobile number whatsapp)              4
how to become Amber Heard 's' husbannd ( +91 9116496706 clontact phone / mobile number whatsapp)            4
revenge spell for Amber Heard ( +91 9116496706 clontact phone / mobile number whatsapp)                     4
whats Amber Heard ' s phone / mobile number ( +91 9116496706 clontact phone / mobile number whatsapp)       4
Name: text, dtype: int64


df_users[df_users.user_name == 'Dannig178']


df_dannig = df.query(" author == 'Dannig178' ").reset_index(drop=True)
print(df_dannig.shape)
df_dannig.head()

(70, 17)


df_dannig.subreddit.value_counts().head(10)

r/BralessCelebs          7
r/CelebritiesBarefoot    7
r/celebheels             7
r/celeb_nylons           7
r/celeb_underwear        7
r/handbra                5
r/Celebs                 4
r/CelebrityButts         4
r/CelebrityPokies        3
r/celebritylegs          3
Name: subreddit, dtype: int64


df_dannig.submission_comment.value_counts()

submission    67
comment        3
Name: submission_comment, dtype: int64


df_dannig.text.value_counts().head(10)

Amber Heard           67
FMK                    1
Amber                  1
/r/celeb_underwear     1
Name: text, dtype: int64


df_dannig_contributions = df_dannig.groupby(df_dannig.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_dannig_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Dannig178" contributions in 2021')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_dannig_contributions.created_at,
    )
)

fig.update_traces(marker_color='red', marker_line_width=1, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


df_dannig_contributions.sort_values('n_contributions', ascending=False).head(10)


# check the date this account was creted
df_users[df_users.user_name == '5th_Law_of_Robotics']


df_law = df.query(" author == '5th_Law_of_Robotics' ").reset_index(drop=True)
print(df_law.shape)
df_law.head()

(68, 17)


df_law.submission_comment.value_counts()

comment       62
submission     6
Name: submission_comment, dtype: int64


df_law.subreddit.value_counts().head(10)

r/WeinsteinEffect      39
r/MensRights           10
r/Egalitarianism        7
r/entertainment         7
r/Toxic_Femininity      3
r/ProMaleCollective     1
r/RedditCensors         1
Name: subreddit, dtype: int64


df_law.text.value_counts().head(10)

Petition To Remove 'Accused DV Perpetrator' Amber Heard from Aquaman 2                                                                                                                                                                                                                                                                                 2
Amber Heard Worried She Will Be 'Demonized' In Johnny Depp Lawsuit, Wants Details Kept Private                                                                                                                                                                                                                                                         2
So you don't know what a comparison is?                                                                                                                                                                                                                                                                                                                1
Johnny didn't do anything wrong.                                                                                                                                                                                                                                                                                                                       1
>Depp still has a violent past though.   \n\n\nElaborate.\n\n\n>You just need to believe that. \n\n\nSo you believe he abused her based on what?\n\n                                                                                                                                                                                                   1
Johnny Depp Scores a Victory in Amber Heard $50 Million Defamation Lawsuit                                                                                                                                                                                                                                                                             1
So you won't answer in good faith. Noted.\n\n\n"All the time" is an expression that isn't meant literally every instant always.\n\n\nPeople fall in love all the time doesn't mean everyone is in love at any given second.\n\n\nWould you correct a BLM activist who said blacks are profiled all the time?                                           1
>Not only is that article from over four years ago,\n\nStill relevant.\n\n\n> but it's not about RAINN.\n\n\nIt does reference RAINN as the source for the stats.\n\n\nYou could also go look at their posted methodology. That's what I did.                                                                                                          1
He means the divorce hearing.\n\n\nShe filed a restraining order when they separated then agreed to drop it for 7 million.\n\n\nIt's interesting according to Wikipedia all Johnny's friends begged him not to marry her without a prenup. He ignored them and she left within a year with significant financial gain.                                 1
I've been told longer sentences for the same crime and lower graduation rates are male privileges. So that.\n\n\nAnd if you're in a job requiring a suit every day you are privileged to be forced to wear a suit and be comfortable with lower AC temps while women are oppressed with choices, some of which have the consequence of being cold.     1
Name: text, dtype: int64


df_law_contributions = df_law.groupby(df_law.created_at.dt.date).size().reset_index(name='n_contributions')
df_law_contributions.sort_values('n_contributions',ascending=False)


fig = px.bar(df_law_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "5th_Law_of_Robotics" contributions in 2021')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_law_contributions.created_at,
    )
)

fig.update_traces(marker_color='red',
                  marker_line_width=2, opacity=1, textposition='auto')
fig.show()


df_law_contributions


df_news = df.query(" author == 'newsfeedmedia' ").reset_index(drop=True)
print(df_news.shape)
df_news.head()

(62, 17)


df_news.subreddit.value_counts().head(10)

r/newsfeedmedia    62
Name: subreddit, dtype: int64


df_news.submission_comment.value_counts()

submission    62
Name: submission_comment, dtype: int64


df_news['permalink'].iloc[5]

'/r/newsfeedmedia/comments/b1513g/amber_heard_seen_sharing_a_passionate_kiss_with/'


df_news.text.value_counts().head(10)

Amber Heard comforted after lawyer meeting… amid $50million defamation lawsuit from ex Johnny Depp    1
Amber Heard is spotted out with rumored beau Andy Muschietti amid Johnny Depp lawsuit drama           1
Amber Heard looks radiant in cream blouse during Cannes Film Festival                                 1
Bella Hadid and Amber Heard sizzle at the Pain and Glory premiere during Cannes Film Festival         1
Amber Heard showcases her incredible figure in a tiny red bikini on a yacht in the Amalfi Coast       1
Amber Heard hints at legal troubles with ex-husband Johnny Depp                                       1
Amber Heard rocks a chic skirt with leg slit after launching initiative to help women in Lebanon      1
Amber Heard looks ready for business in a black suit as she lands in New York                         1
Amber Heard says Johnny Depp is refusing to provide evidence                                          1
Amber Heard and James Marsden to star in remake of Stephen King’s The Stand                           1
Name: text, dtype: int64


df_news_contributions = df_news.groupby(df_news.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_news_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "newsfeedmedia" contributions in 2021')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_news_contributions.created_at,
    )
)

fig.update_traces(marker_color='red', marker_line_width=2, opacity=1) 
# , marker_line_color='#5296dd'

fig.show()


df_news_contributions.sort_values('n_contributions', ascending=False).head(10)


df_saku = df.query(" author == 'SakuOtaku' ").reset_index(drop=True)
print(df_saku.shape)
df_saku.head()

(57, 17)


df_saku.subreddit.value_counts().head(10)

r/WeinsteinEffect    48
r/movies              4
r/GamerGhazi          4
r/harrypotter         1
Name: subreddit, dtype: int64


df_saku.submission_comment.value_counts()

comment       54
submission     3
Name: submission_comment, dtype: int64


df_saku['permalink'].iloc[5]

'/r/WeinsteinEffect/comments/b0h5wa/why_some_people_are_uncanceling_johnny_depp_in/eiemnna/'


df_saku.text.value_counts().head(5)

As someone who first brought the newer parts of the story to the sub, I don't think it fits anymore. It's domestic violence, yes, but at this point, it's not really so much a Weinstein-esque thing as it is a court case where both sides are accusing the other. \n\nIf this gets removed, then it's not because people don't acknowledge male victimhood. It's mostly because this story just doesn't really fit here at this point.                                                                                                                                                                                                                                                                                                                                                                                                                     1
Two different sources, both made to look like victims lie on average. I've been on RAINN's site before, the low conviction rate is due to the difficulty of proving rape (rape kits have to be done in a very short span of time iirc). The FBI may be counting "false" as cases where the alleged rapist wasn't convicted. Aka you cherry picked.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           1
Before it seemed like this case was heading into the "he tried to silence her" direction. Now it's moved from that. Even initially in 2016 the case wouldn't have belonged here. It went from domestic to power related back to domestic.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    1
Even if it was removed,  this topic has already been covered here to the fullest extent it can be at this stage. We still don't know who's telling the truth, there's been no verdict. \n\nTo re-cover the story every time Depp counter alleges something is just gossipy journalism pandering to MRAs or people who've already made up their minds before the trial is over. We need to wait and see. \n\nCase in point,  not to get salty over lack of karma but posts like these barely having to do with this sub get hundreds of upvotes while I posted something the other day involving a well known internet celebrity who sent nudes to fans who were minors (using power to commit sex crimes) and it got a whopping 10 upvotes.\n\n I'm not concerned because it was my post, but it seems like gossip is starting to trump relevant content.    1
This whole case is just strange to me- mostly because I used to really really like Johnny Depp before all of this. Idk at the time, it *really* did seem like he was guilty. Idk currently going off of that initial trial and what's happening now, I'm guessing it was mutual maybe (with the whole "neither of us was lying" thing, etc) but frankly I think I'll wait and see before I make any further judgments.                                                                                                                                                                                                                                                                                                                                                                                                                                       1
Name: text, dtype: int64


df_saku_contributions = df_saku.groupby(df_saku.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_saku_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "SakuOtamu" contributions in 2021')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_saku_contributions.created_at,
    )
)

fig.update_traces(marker_color='red', marker_line_width=2, opacity=1) 
# , marker_line_color='#5296dd'

fig.show()


df_saku_contributions.sort_values('n_contributions', ascending=False).head(10)


df_sov = df.query(" author == 'Sovetika' ").reset_index(drop=True)
print(df_sov.shape)
df_sov.head()

(48, 17)


df_sov.submission_comment.value_counts()

submission    48
Name: submission_comment, dtype: int64


df_sov.subreddit.value_counts().head(10)

r/STRANI       23
r/SOVETIKA     17
r/lukomorye     8
Name: subreddit, dtype: int64


df_sov['permalink'].iloc[5]

'/r/lukomorye/comments/axctrj/amber_heard_z1016/'


df_sov.text.value_counts().head(5)

Amber Heard (s381) | Sovetika.ru - знаменитости    1
Amber Heard - s244 | Strani.ru - gallery           1
Amber Heard - s246 | Strani.ru - gallery           1
Amber Heard - s241 | Strani.ru - gallery           1
Amber Heard (s372) | Sovetika.ru - знаменитости    1
Name: text, dtype: int64


df_sov_contributions = df_sov.groupby(df_sov.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_sov_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Sovetika" contributions in 2021')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_sov_contributions.created_at,
    )
)

fig.update_traces(marker_color='red', marker_line_width=2, opacity=1) 
# , marker_line_color='#5296dd'

fig.show()


df_sov_contributions.sort_values('n_contributions', ascending=False).head(10)


df.author.value_counts().nlargest(n=25)

-banned-               4487
AutoModerator           426
CelebBattleVoteBot      120
spells010                80
Dannig178                70
5th_Law_of_Robotics      68
newsfeedmedia            62
SakuOtaku                57
Sovetika                 48
bufedad                  43
DerHander                41
RuleIV                   40
guac_boi1                36
AutoNewsAdmin            36
AutoNewspaperAdmin       34
Pixelated_Piracy         34
InfiniTitans             32
majortom106              30
bitcoinwallpaper2        30
sweetestdeth             30
juanathanluis            30
Rednaxela117             28
reignkaera               28
GRJR721                  26
HawkofDarkness           26
Name: author, dtype: int64


check_list = df.author.value_counts().nlargest(n=25).index.tolist()[1:]
set(check_list)

{'5th_Law_of_Robotics',
 'AutoModerator',
 'AutoNewsAdmin',
 'AutoNewspaperAdmin',
 'CelebBattleVoteBot',
 'Dannig178',
 'DerHander',
 'GRJR721',
 'HawkofDarkness',
 'InfiniTitans',
 'Pixelated_Piracy',
 'Rednaxela117',
 'RuleIV',
 'SakuOtaku',
 'Sovetika',
 'bitcoinwallpaper2',
 'bufedad',
 'guac_boi1',
 'juanathanluis',
 'majortom106',
 'newsfeedmedia',
 'reignkaera',
 'spells010',
 'sweetestdeth'}


# get a data frame with the most negative-comments users
df_check = df_users[df_users['user_name'].isin(check_list)]
print(df_check.shape)
df_check.head(2)

(24, 10)


df_check['user_name'].nunique()

24


def get_stats(df):
    for col in df.columns:
        if col not in ['user_name', 'user_created_at']:
            if col not in ['link_karma', 'comment_karma']:
                print('The value counts of the users with the most contributions: ' + col)
                print(df_check[col].value_counts())
                print('\n')
                
            else:
                print("The min of {}".format(col), round(df_check[col].min(),2))
                print('\n')
                print("The max of {}".format(col), round(df_check[col].max(),2))
                print('\n')
                print("The mean of {}".format(col), round(df_check[col].mean(),2))
                print('\n')
                print("The median of {}".format(col), round(df_check[col].mean(),2))
                print('\n')


get_stats(df_check)

The value counts of the users with the most contributions: has_verified_email
True     23
False     1
Name: has_verified_email, dtype: int64


The value counts of the users with the most contributions: is_mod
True     16
False     8
Name: is_mod, dtype: int64


The value counts of the users with the most contributions: is_gold
False    20
True      4
Name: is_gold, dtype: int64


The value counts of the users with the most contributions: is_banned
False    23
True      1
Name: is_banned, dtype: int64


The min of comment_karma 0.0


The max of comment_karma 155384.0


The mean of comment_karma 29462.35


The median of comment_karma 29462.35


The min of link_karma 1.0


The max of link_karma 982410.0


The mean of link_karma 133463.65


The median of link_karma 133463.65


The value counts of the users with the most contributions: banned_unverified
others        22
unverified     1
banned         1
Name: banned_unverified, dtype: int64


The value counts of the users with the most contributions: creation_year
others    17
2018       3
2019       3
banned     1
Name: creation_year, dtype: int64


# pd.set_option('display.max_colwidth', None)
suspected_dict = {}


df_fuc = df[df.text.str.lower().str.contains('fuck')]
print(df_fuc.shape)
df_fuc.head()

(1254, 17)


# get the authors of these submissions having the same submission text

mask = (df['submission_text'] == 'fuck_amber_heard') & (df['submission_comment'] == 'submission')
df_sub = df[mask]
print(df_sub.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_sub.head())

(1, 17)


# get the authors of these submissions having the same submission text

mask = (df['submission_text'].str.contains('fuck')) & (df['submission_comment'] == 'submission')
df_sub_fuc = df[mask]
print(df_sub_fuc.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_sub_fuc.head())

(37, 17)


df_sub_fuc_contributions = df_sub_fuc.groupby(df_sub_fuc.created_at.dt.date).size().reset_index(name='n_contributions')

fig = px.bar(df_sub_fuc_contributions,
             x='created_at', 
             y='n_contributions', title='The number of submissions with the word "F*CK" in 2019')
fig.update_traces(marker_color='red', marker_line_width=.5, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


df_sub_fuc_contributions.sort_values('n_contributions', ascending=False)


df_fuc.author.value_counts().head(10)

-banned-                258
juanathanluis            11
armoured_bobandi          9
Ryggg95                   7
SexBoi6969                6
flightfight1              5
ForensicatingEdibles      5
xRisingSunx               5
pervaccount123            5
funlover24                4
Name: author, dtype: int64


df_fuc.submission_comment.value_counts()

comment       1204
submission      50
Name: submission_comment, dtype: int64


df_fuc.subreddit.value_counts().head(10)

r/movies               198
r/JerkOffToCelebs      185
r/CelebEconomy         140
r/entertainment        138
r/MensRights            82
r/pussypassdenied       61
r/worldnews             60
r/television            31
r/WatchItForThePlot     26
r/gentlemanboners       25
Name: subreddit, dtype: int64


df_fuc.created_at.dt.date.value_counts().head(10)

2019-03-15    189
2019-03-14     99
2019-03-13     81
2019-03-16     44
2019-08-03     25
2019-03-04     22
2019-03-03     20
2019-06-25     19
2019-03-24     19
2019-07-11     18
Name: created_at, dtype: int64


df_fuc_contributions = df_fuc.groupby(df_fuc.created_at.dt.date).size().reset_index(name='n_contributions')

fig = px.bar(df_fuc_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "F*CK" contributions in 2019')
fig.update_traces(marker_color='red', marker_line_width=1, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


df_fuc_contributions.sort_values('n_contributions', ascending=False).head(10)


df_juan = df.query(" author == 'juanathanluis' ")
print(df_juan.shape)
df_juan.head()

(30, 17)


df_juan.created_at.dt.date.value_counts()

2019-01-28    3
2019-02-22    3
2019-04-15    2
2019-03-25    2
2019-10-07    2
2019-10-05    2
2019-12-10    1
2019-01-08    1
2019-10-11    1
2019-06-28    1
2019-06-17    1
2019-01-02    1
2019-05-22    1
2019-01-31    1
2019-10-16    1
2019-08-30    1
2019-08-03    1
2019-05-01    1
2019-06-25    1
2019-06-26    1
2019-02-01    1
2019-10-27    1
Name: created_at, dtype: int64


df_juan.subreddit.value_counts()

r/CelebEconomy          13
r/pickoneceleb           8
r/TrueFMK                7
r/JerkOffToCelebs        1
r/CelebAssPussyMouth     1
Name: subreddit, dtype: int64


df_juan.text.value_counts().head(3)

Anal - Taylor because she needs a rough fuck. \n\nBlowjob - Cameron because she’s got nice lips. \n\nTitfuck - Eva, [obviously](https://gfycat.com/ForkedCaringFirefly). \n\nDoggystyle - Emilia, to recreate [this scene](https://gfycat.com/lawfulsneakygermanspitz). \n\nMissionary - Amber because she’s beautifully bland. \n\nBDSM - Zoe because she’s a strong woman who would be a good dom. \n\nPussy eating - Jennifer Lawrence because her and Emma are the last ones left and i want to rawdog Emma. \n\nRawdog - Emma because I love her and wouldn’t mind impregnating her.                                                                                                                                                                                             2
**Lili Reinhart** (5) Eat her out (2) = $10\n\n**Eiza Gonzalez** (10) Doggystyle and creampie (3) = $30\n\n**Alexandra Daddario** (20) Cowgirl and creampie (3) = $60                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 1
Great post OP. \n\n1. Emma Watson just so I can listen to the British accent. \n\n2. Bella Thorne because she’s trashy. \n\n3. Amber Heard and Kay Dennings because why not. \n\n4. Megan Fox. Shrugs. \n\n5. Brie Larson because I probably won’t be to turned on by her. \n\n6. Victoria Justice and I would date her long term before leaving her for Ana de Armas. \n\n7. Kate Beckinsale, Jennifer Lawrence, Blake Lively. I skipped this one and did it last. These were the three remaining girls. I’m pretty happy about it being these three. \n\n8. Mary Elizabeth Winstead because she was my number two choice for 10. \n\n9. Katy Perry and Taylor Swift because their enemies and I want them to fight over me. \n\n10. Ana de Armas because i am in love with her.     1
Name: text, dtype: int64


df_users[df_users.user_name == 'juanathanluis']


df.text.value_counts().head(25)

Amber Heard                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    1832
[deleted]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       645
[removed]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       233
**Thank you for your submission. Make sure to follow the rules.**\n\n**Don't forget to follow us on [Instagram](https://www.instagram.com/jotocelebs/) and [join our Discord Server](https://discord.gg/PrRFWsa)!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/JerkOffToCelebs) if you have any questions or concerns.*                                                                            64
Remember to keep comments civil.\n\n**[Follow our Instagram page](https://www.instagram.com/celebtag/) for more celebrity content and daily top posts!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/Celebhub) if you have any questions or concerns.*                                                                                                                                              59
**Thank you for your submission. Make sure to follow the rules.**\n\n**Check out our [FAP LOTTERY!](https://jerkofftocelebs.com/)**\n\n**Don't forget to follow us on [Instagram](https://www.instagram.com/jotocelebs/) and [join our Discord Server](https://discord.gg/PrRFWsa)!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/JerkOffToCelebs) if you have any questions or concerns.*          54
KMF                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              53
FKM                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              52
Amber                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            47
FMK                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              45
KFM                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              42
**Thank you for your submission. Make sure to follow the rules.**\n\n**Check out our [NEW FAP LOTTERY!](https://jerkofftocelebs.com/)**\n\n**Don't forget to follow us on [Instagram](https://www.instagram.com/jotocelebs/) and [join our Discord Server](https://discord.gg/PrRFWsa)!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/JerkOffToCelebs) if you have any questions or concerns.*      40
MKF                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              39
MFK                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              38
Amber heard                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      38
Margot                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           33
Johnny Depp was abused by ex-wife Amber Heard, new evidence shows                                                                                                                                                                                                                                                                                                                                                                                                                                29
Gal                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              23
Amber Heard - The Informers                                                                                                                                                                                                                                                                                                                                                                                                                                                                      19
Amber Heard in The Informers                                                                                                                                                                                                                                                                                                                                                                                                                                                                     17
Make sure to follow our community guidelines.\n\n**[Get user flair](https://redd.it/e0a4mn) and [check out our Instagram page](https://www.instagram.com/celebtag/) for more celebrity content!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/Celebhub) if you have any questions or concerns.*                                                                                                     17
Scarlett                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         17
[Aquaman] Amber Heard                                                                                                                                                                                                                                                                                                                                                                                                                                                                            14
Fmk                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              14
Your comment has been removed due to your account not meeting the required (> 7 day old) limit necessary to post here\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/JerkOffToCelebs) if you have any questions or concerns.*                                                                                                                                                                            13
Name: text, dtype: int64


text = "Amber Heard".lower()

df_amber = df[df.text.str.lower().str.contains(text)]

print(df_amber.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_amber.head())

(4641, 17)


df_amber.subreddit.value_counts()

r/Celebs             532
r/gentlemanboners    317
r/JerkOffToCelebs    271
r/Celebhub           222
r/CelebBattles       140
                    ... 
r/redrising            1
r/Elsas                1
r/NSFWBOX              1
r/blueeyedgirls        1
r/autotldr             1
Name: subreddit, Length: 531, dtype: int64


df_amber.author.value_counts().head(10)

-banned-              1396
spells010               80
Dannig178               67
newsfeedmedia           62
CelebBattleVoteBot      55
Sovetika                48
AutoNewsAdmin           36
AutoNewspaperAdmin      34
bitcoinwallpaper2       30
DerHander               30
Name: author, dtype: int64


df_users.query("user_name in ['spells010', 'Dannig178']")


text1 = "fmk"
text2 = 'fkm'
text3 = "mfk"
text4 = 'kfm'

df_fmk = df[(df.text.str.lower().str.contains(text1)) |
           (df.text.str.lower().str.contains(text2)) | 
           (df.text.str.lower().str.contains(text3)) |
           (df.text.str.lower().str.contains(text4))]

print(df_fmk.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_fmk.head())

(311, 17)


df_fmk.author.value_counts().head(20)

-banned-              23
AutoModerator         21
FMKBot                11
billysuperduper        6
naedthrowaway          6
throwedrollss          6
MerlinRD               5
PM_ME_UR_PIG-TAILS     5
Narfle_TheGarthok      5
herkalurk              5
GrotAcc                4
sullima2014            4
sirentdead             4
OrangePaper300         4
dklement               4
rotten_person          4
smithjason151          3
A_Tribute_For_You      3
zorbathegrate          3
DarthVilgrath101       3
Name: author, dtype: int64


fmk_list = ['AutoModerator', 'FMKBot']


fmk_list

['AutoModerator', 'FMKBot']


df_users[df_users['user_name'].isin(fmk_list)]


df_fmk_contributions = df_fmk.groupby(df_fmk.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_fmk_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "FMK, KFM ..etc" contributions in 2019')
fig.update_traces(marker_color='red', marker_line_width=0.5, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


text = "fuck amber heard"

df_fuc2 = df[df.text.str.lower().str.contains(text)]

print(df_fuc2.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_fuc2.head())

(32, 17)


df_fuc2.author.value_counts()

-banned-                10
ADM86                    2
RossSkyWalkerr           2
orton41290               1
BeefStrykker             1
flightfight1             1
Ninja_Arena              1
Jacknatureboy            1
Willkthewpboy            1
selenakyleprrrr          1
Count_Fapula1            1
Sayena08                 1
MeC0195                  1
nodeofollie              1
Tramm                    1
BiggerDamnederHeroer     1
_Not_Bruce_Wayne_        1
Iconoficons              1
Inshabel                 1
sev1nk                   1
KFBR392GoForGrubes       1
Name: author, dtype: int64


df_fuc2.subreddit.value_counts()

r/JerkOffToCelebs    11
r/movies              5
r/MensRights          4
r/nsfwcelebs          2
r/television          2
r/rant                1
r/teenagers           1
r/gentlemanboners     1
r/Feminism            1
r/pics                1
r/JordanPeterson      1
r/entertainment       1
r/WeinsteinEffect     1
Name: subreddit, dtype: int64


df_fuc2.subreddit.value_counts();


df_fuc2_submissions = df_fuc2.query(" submission_comment == 'submission' ")
print(df_fuc2_submissions.shape)
df_fuc2_submissions.head()

(11, 17)


df_fuc2_submissions.author.value_counts()

-banned-          6
RossSkyWalkerr    2
Count_Fapula1     1
flightfight1      1
Jacknatureboy     1
Name: author, dtype: int64


text = "[Aquaman] Amber Heard".lower()

df_aqua = df[df.text.str.lower().str.contains(text)]

print(df_aqua.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_aqua.head())

(115, 17)


df_aqua.created_at.dt.date.value_counts().head(10)

2019-10-15    12
2019-10-19    11
2019-04-22    11
2019-03-15     8
2019-10-22     7
2019-10-24     6
2019-03-13     6
2019-03-14     5
2019-02-01     3
2019-05-21     2
Name: created_at, dtype: int64


df_aqua.subreddit.value_counts().head(10)

r/BitcoinWallpaper    44
r/EcuadorNoticias     11
r/movies               6
r/JerkOffToCelebs      6
r/AskReddit            5
r/DC_Cinematic         5
r/gentlemanboners      4
r/entertainment        4
r/television           3
r/MensRights           2
Name: subreddit, dtype: int64


df_aqua.author.value_counts().head(10)

bitcoinwallpaper2    26
-banned-             14
spastorm20           11
bitcoinwallpaper     10
bitcoinwallpaper3     7
i_am_leatherface      3
bufedad               3
Fgge                  1
Waluigi2049           1
KrissyB93             1
Name: author, dtype: int64


df_users[df_users.user_name == 'bitcoinwallpaper2']


df_aqua[df_aqua.author == 'bitcoinwallpaper2'].created_at.dt.date.value_counts()

2019-10-22    6
2019-10-15    6
2019-10-19    6
2019-10-24    6
2019-10-12    1
2019-10-14    1
Name: created_at, dtype: int64


df_aqua[df_aqua.author == 'bitcoinwallpaper2'].subreddit.value_counts()

r/BitcoinWallpaper    26
Name: subreddit, dtype: int64


df_aqua[df_aqua.author == 'bitcoinwallpaper2'].submission_comment.value_counts()

submission    26
Name: submission_comment, dtype: int64


text = "ex-wife".lower()

df_her = df[df.text.str.contains(text)]
# df_her = df_her.sort_values('created_at')

print(df_her.shape)
df_her.head()

(154, 17)


df_her.text.values

array(['For those who dont wanna click and are out of the loop like myself. \n\nJohnny Depp\xa0has filed a defamation lawsuit against his ex-wife,\xa0Amber Heard, alleging\xa0her domestic abuse claims were “an elaborate hoax” and he is going after her for a whopping $50 million',
       'Johnny Depp sues ex-wife Amber Heard for $50million over abuse claims',
       'Johnny Depp sues ex-wife Amber Heard for $50million over abuse claims',
       'Using finances to threaten, intimidate, or hurt someone is a classic tactic of abusers. Suing for defamation is one thing, but $50 million 3+ years after everything went down just reeks of vindictiveness. *At best* I could see a scenario where they were mutually abusive, but considering Depp’s obvious drug use and erratic behavior (and this latest bout of post-divorce pettiness) I lean more towards believing Heard’s account of things.\n\nEDIT: Take the time to look into why Depp is actually suing her. It’s over this op-ed: https://www.washingtonpost.com/opinions/ive-seen-how-institutions-protect-men-accused-of-abuse-heres-what-we-can-do/2018/12/18/71fd876a-02ed-11e9-b5df-5d3874f1ac36_story.html?utm_term=.6d2ded819b3b\n\nThat opinion piece on speaking out about sexual assault and violence is *literally* what Depp and his lawyer are listing as their reason for suing her:\n\n“Johnny Depp is demanding damages from ex-wife Amber Heard after she wrote an op-ed characterizing herself as a domestic abuse victim.”\n\nhttps://people.com/movies/johnny-depp-50-million-defamation-lawsuit-amber-heard/\n\nShe says she became a “public figure that represented domestic abuse”, which regardless of whether or not she was abused *is a true statement*. That statement is why she’s being sued *for $50 million*. This lawsuit is going to fail, because it is ludicrous. The more I read about it the more obviously vindictive, petty, and controlling it is.',
       "[Arts] - Johnny Depp sues ex-wife Amber Heard for $50m over 'hoax' domestic abuse claims",
       "[Arts] - Johnny Depp sues ex-wife Amber Heard for $50m over 'hoax' domestic abuse claims | The Independent",
       'You mean this: https://www.washingtonpost.com/opinions/ive-seen-how-institutions-protect-men-accused-of-abuse-heres-what-we-can-do/2018/12/18/71fd876a-02ed-11e9-b5df-5d3874f1ac36_story.html?utm_term=.6d2ded819b3b\n\nBecause that opinion piece on speaking out about sexual assault and violence is *literally* what Depp and his lawyer are listing as their reason for suing her:\n\n“Johnny Depp is demanding damages from ex-wife Amber Heard after she wrote an op-ed characterizing herself as a domestic abuse victim.”\n\nhttps://people.com/movies/johnny-depp-50-million-defamation-lawsuit-amber-heard/\n\nThe thing is, the op-ed focuses more on sexual assault from her teens. It’s literally an article about how society at large treats you when you speak out, not an article focusing on Depp. The more I look into this lawsuit the more I feel like this is incredibly vindictive, petty, and controlling on Depp’s end.',
       'Johnny Depp sues ex-wife Amber Heard over article',
       'Johnny Depp sues ex-wife Amber Heard over article',
       '[World] - Johnny Depp sues ex-wife Amber Heard over article',
       'Johnny Depp sues ex-wife Amber Heard over article',
       '@BBCWorld: Johnny Depp sues ex-wife Amber Heard over article https://t.co/goZQapC5Q8',
       '[World] - Johnny Depp sues ex-wife Amber Heard over article | BBC',
       'Johnny Depp sues ex-wife Amber Heard over article',
       '‘An elaborate hoax’: Johnny Depp sues ex-wife Amber Heard for US$50 million in defamation suit over article on domestic abuse',
       '[World] - ‘An elaborate hoax’: Johnny Depp sues ex-wife Amber Heard for US$50 million in defamation suit over article on domestic abuse',
       '[World] - ‘An elaborate hoax’: Johnny Depp sues ex-wife Amber Heard for US$50 million in defamation suit over article on domestic abuse | South China Morning Post',
       'Johnny Depp sues ex-wife Amber Heard and claims Elon Musk was sleeping with Amber while they were married in their own house.',
       'Johnny Depp sues ex-wife Amber Heard for $50M, claiming defamation, affair with Elon Musk',
       'Johnny Depp sues ex-wife Amber Heard for $50M, claiming defamation, affair with Elon Musk',
       'Johnny Depp sues ex-wife Amber Heard for $50M, claiming defamation, affair with Elon Musk - Fox News',
       'Johnny Depp claims ex-wife Amber Heard had an affair with Elon Musk',
       "I found some links for you and one of them mentioned an affai with Ellon musk so I'm skeptical but there were a lot of articles about it when I only typed in Johnny Depp lawsuit Amer\nhttps://www.bbc.co.uk/news/amp/world-us-canada-47426674\n\nhttps://www.news.com.au/entertainment/celebrity-life/celebrities-gone-bad/johnny-depp-has-sued-former-wife-amber-heard-for-50m/news-story/f9255f471f41965a21bfe1cbe52675e2\n\nhttps://www.foxnews.com/entertainment/johnny-depp-sues-ex-wife-amber-heard-for-50m-claiming-defamation-affair-with-elon-musk\n\nAnd there's a single one that says 70M\n\nhttps://www.news.com.au/entertainment/celebrity-life/johnny-depp-files-70m-lawsuit-against-exwife-amber-heard/news-story/b5957e14b9b29388206deb94035663c4",
       'Johnny Depp sues ex-wife Amber Heard, accuses her of cheating on him with Elon Musk',
       'Johnny Depp sues ex-wife Amber Heard for $50M, claiming defamation, affair with Elon Musk - Fox News',
       '[Entertainment] - Johnny Depp sues ex-wife Amber Heard for $50 million in defamation suit',
       'Johnny Depp sues ex-wife Amber Heard, accuses her of cheating on him with Elon Musk - Channel NewsAsia',
       "Johnny Depp claims ex-wife Amber Heard had an affair with Elon Musk and received 'late night' visits from the Tesla founder while the actor was away filming",
       '@ABC: Johnny Depp sues ex-wife Amber Heard, claiming her allegations of abuse were false. https://t.co/RdRhG7lo0V https://t.co/ih4pUC2xjV',
       '[Entertainment] - Johnny Depp sues ex-wife Amber Heard, claiming her allegations of abuse were false',
       '[Entertainment] - Johnny Depp sues ex-wife Amber Heard, claiming her allegations of abuse were false | ABC',
       '[Entertainment] - WATCH: Johnny Depp sues ex-wife Amber Heard, claiming her allegations of abuse were false',
       '[Entertainment] - WATCH: Johnny Depp sues ex-wife Amber Heard, claiming her allegations of abuse were false | ABC',
       'Johnny Depp sues ex-wife Amber Heard Over Me Too Article',
       'Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him',
       'Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him',
       '[Entertainment] - Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him',
       'Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him',
       '@NBCNews: Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him with false allegations of abuse. https://t.co/OYEwmxhPJu',
       'Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him',
       '[Entertainment] - Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him | NBC',
       "03-04 22:12 - 'Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him' (nbcnews.com) by /u/WriterDave removed from /r/news within 102-112min",
       '[Top Stories] - Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him',
       'Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him',
       '@NBCNews: Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him with false allegations of abuse. https://t.co/cOI6R2Kv2S',
       '[Entertainment] - Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him',
       '[Entertainment] - Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him | NBC',
       '[Entertainment] - Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him',
       '[Entertainment] - Johnny Depp sues ex-wife Amber Heard for $50 million for allegedly defaming him | NBC',
       "let's not get ahead of ourselves here. Johnny Depp has yet to prove anything just like his ex-wife had never proved anything. Why don't we let the courts go through the evidence and come to a conclusion before we start getting ahead of ourselves and breaking out the pitchforks.",
       'He is suing HER for $50mil as part of a defamation lawsuit:\n\nhttps://www.nme.com/news/johnny-depp-reportedly-suing-ex-wife-amber-heard-50m-defamation-lawsuit-2456290\n\nShe wrote a WaPo article about the MeToo movement and what it\'s like for women who claim to have been domestically or sexually abused. He\'s suing her for a sentence stating she became "a public figure representing domestic abuse". It\'s been in the news, and the front page of Reddit, for weeks.\n\nHe is also suing The Sun.',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows | Entertainment - Geo.tv',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Shit. That literally helped me out an hour ago. Soon to be ex-wife with her untreated mental health issues wanted to amend the restraining order I have against her to see the dog, and I had her on video violating it back in January.\n\nJudge told her she was an idiot, in her own professional way. ',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       "This story infuriates me. My ex-wife would pull the same things to try and trap me. It got to the point where I had to record phone calls and conversations and take pictures of the damage she had done because I was so afraid she would blame me. Luckily it's saved me when she filed a false police report eventually. \n\nReally bothers me our society's view on female to male domestic violence. She would brag to her coworkers about the thing she would do to me and they thought it was funny that I would complain about it. I'm glad Johnny was smart enough to cover his ass. I can only hope Amber ends up in jail. Most likely her spoiled white girl syndrome will save her oh, just like my ex. ",
       "03-14 15:23 - 'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows' (geo.tv) by /u/Soupjoe5 removed from /r/worldnews within 80-90min",
       '[#23|+3390|554] Johnny Depp was abused by ex-wife Amber Heard, new evidence shows [/r/worldnews]',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Ah, yes, a totally unbiased reading of the "evidence" from Pakistan\'s own GeoTV.\n\nRegardless of how this shakes out, it\'s pretty funny to watch commentators like the tweets in the article talking about how "the internet" and "the media" are so gullible and automatically take as gospel the testimony of any woman claiming to be a victim, citing... nothing but the testimony of a man saying otherwise as evidence that it\'s a lie. \n\nThe obviousness of your bias is just as clear as the obviousness of the bias you\'re calling out, that\'s why you have to go to Pakistani websites to find reporting like this since every reputable source will use cover it like [this](https://www.nbcnews.com/news/us-news/johnny-depp-sues-ex-wife-amber-heard-50-million-allegedly-n978976). Since it is, you know, unsubstantiated allegations backed up with evidence and testimony just as ambiguous as the evidence she entered. Unconfirmable photos of injuries, testimony from friends and staff, she had those things as evidence, too.',
       "Because real news sources are reporting it [like this.](https://www.nbcnews.com/news/us-news/johnny-depp-sues-ex-wife-amber-heard-50-million-allegedly-n978976) Because the evidence is no more compelling than the evidence she entered in her suit and you'd have to have a vested interest in women claiming to be victims of domestic abuse being liars to report on it this way.",
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       '[Johnny Depp sues ex-wife Amber Heard in $50 million defamation suit](https://globalnews.ca/news/5016086/johnny-depp-amber-heard-defamation/) - Global News, March 2, 2019\n\n[Johnny Depp sues ex-wife for $50 million in defamation suit](https://www.ctvnews.ca/entertainment/johnny-depp-sues-ex-wife-for-50-million-in-defamation-suit-1.4319896) - CTV News, March 2, 2019\n\nIt has, just not American ones.',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp accuses ex-wife Amber Heard of abuse, chopping his finger',
       '> Hollywood actor Johnny Depp had been embroiled in a controversy after his ex-wife Amber Heard accused him of domestic abuse last year, in an op-ed penned in the Washington Post. Things seem to have turned around, however, with Depp suing Amber for $50 million for defamation.\n\n> Depp\'s lawsuit referred to Heard\'s allegations as a \'hoax\' and has presented new evidence that it was actually Depp who was physically abused in the marriage, and not the other way around. "Ms. Heard also knew that her elaborate hoax worked: As a result of her false allegations against Mr. Depp, Ms. Heard became a darling of the #MeToo movement, was the first actress named a Human Rights Champion of the United Nations Human Rights Office, was appointed ambassador on women\'s rights at the American Civil Liberties Union, and was hired by L\'Oreal Paris as its global spokesperson," the lawsuit stated.\n\n> Depp\'s legal team have provided fresh evidence alleging Heard punched Depp in the face and and chopped a part of his finger. The new video and photographic evidence submitted show Depp\'s face with a huge bruise, and one of his fingers severed. Depp also submitted 87 surveillance camera videos to the court and 17 depositions of witnesses, including police officers.\n\n> This new development has brought around a change in attitude towards Depp on social media. Fans have been apologising to the actor for accusing him of abuse. According to reports, Depp is \'overwhelmed\' with this outpouring of support.\n\n> This man has been attacked and hated for 3 years while he was the victim, but never stopped being the kind, gentle, sweet human being that he has always been. I\'m so happy to see him healing from all the abused he suffered #JohnnyDepp pic.twitter.com/7kSRm6xWUF\n\n> — Ang_Xim (@Lifeisabirdsong) March 13, 2019\nThe internet of idiots blindly supported Amber and trolled #JohnnyDepp without knowing the truth. https://t.co/GRAS1aGjt6\n\n> — Karthikiyen (@karthikiyen) March 13, 2019\nThis should get more retweets, this is why we\'re here, this is why he\'s suing!!#JohnnyDepp #johnnydeppisinnocent https://t.co/F8wvrobc6m\n\n> — Maya #IBelieveHim (@mayak215) March 13, 2019',
       "> The actor sued his ex-wife for defamation earlier this month\n\n> Details of Johnny Depp‘s defamation lawsuit against Amber Heard have come to light, with the actor accusing his ex-wife of numerous incidents of domestic abuse.\n\n> Depp filed a $50 million lawsuit against Heard on March 1, with the Pirates of the Caribbean star taking action in response to an op-ed Heard penned in 2018 for The Washington Post. Although she didn’t specifically mention Depp by name, the piece refers to the allegations of domestic abuse that Heard first made against the actor in 2016.\n\n> The couple divorced in 2017 after settling both their divorce and Heard’s domestic abuse case against Depp the previous year.\nDepp’s lawsuit has now been made available to view online, with the papers claiming that Heard’s allegations of domestic abuse are nothing more than an “elaborate hoax”.\n\n> “The op-ed depended on the central premise that Ms. Heard was a domestic abuse victim and that Mr. Depp perpetrated domestic violence against her,” the complaint reads, adding that the piece’s implication that Depp was a domestic abuser are “categorically and demonstrably false.”\n\n> “Ms. Heard’s false allegations against Mr. Depp have been conclusively refuted by two separate responding police officers, a litany of neutral third-party witnesses, and 87 newly obtained surveillance camera videos.”\n\n> The suit, which accuses Heard of being a “perpetrator” of domestic abuse, also alleges that Heard attacked Depp numerous times, including an incident where Heard “violently” threw a bottle of vodka at Depp which “severed [his] middle finger on his right hand and shattered the bones,” causing him to require surgery. Heard is also accused of punching Depp while he was in bed, kicking him on numerous occasions and staging attacks.\n\n>“Unaware that members of Mr. Depp’s security team were mere feet away, Ms. Heard falsely began yelling, ‘Stop hitting me, Johnny,'” the documents describe one alleged incident in May 2016. “The interaction culminated with Ms. Heard making false allegations that \nMr. Depp struck her with a cell phone, hit her and destroyed the penthouse. There were multiple eyewitnesses to this hoax.”\n\n> In response to the lawsuit earlier this month, Heard’s attorney Eric M. George told Deadline: “This frivolous action is just the latest of Johnny Depp’s repeated efforts to silence Amber Heard. She will not be silenced.\n\n> “Mr. Depp’s actions prove he is unable to accept the truth of his ongoing abusive behaviour. But while he appears hell-bent on achieving self destruction, we will prevail in defeating this groundless lawsuit and ending the continued vile harassment of my client by Mr. Depp and his legal team.”\n",
       'Johnny Depp files defamation suit against ex-wife Amber Heard',
       'Pakistan is a country with honor killings and incredibly regressive views on women\'s rights, and its news organizations reflect that, as well as the lower standard of journalistic ethics held by many of its publications. \n\nIt\'s relevant because looking at the [top news stories on google for Johnny Depp](https://imgur.com/O6HKFzY) right now **all** of the stories reporting this story in that way are either Pakistani, Nigerian, or American far right propaganda sites. Like, for instance, The Daily Wire that you have cited there, which is owned by Ben Shapiro. \n\nAlmost as if the people that want to present this story in this particular way have a clear agenda. And at least one of the "top stories" (5why.com.au) comes from a website with no google results other than this story and a non-working website. Which looks a lot like a PR campaign using fake news sites and media outlets that actively push an anti-feminist agenda to influence public opinion on this court case and Depp himself.\n\n----------------\n\nThe other two sources you have there simply explain the allegations of the suit, list its supposed evidence, and detail public reaction to it. Which is not the same as saying the very explicit and declarative "Johnny Depp was abused by ex-wife Amber Heard, new evidence shows." Proper journalism would be "Johnny Depp *claims to have been* abused by ex-wife Amber Heard, *according to allegations in new defamation suit*" \n\nThis matter hasn\'t been adjudicated yet, his claims and evidence have been presented to the court but that doesn\'t make it automatically true any more than her claims in court were. It\'s not the role of a journalist to present someone\'s unverified claims as true and if you think this article(or the Daily Caller) is what actual journalism looks like I invite you to consider that maybe you want it to be true.',
       'But Johnny Depp has no history of being accused of domestic violence.Even after being initially accused by her,his exes,including his ex-wife and mother of his children and his daughter supported him and said he would never do that.His close friends too.Not to mention that Amber Heard does have a history of being accused of domestic violence.She was once almost arrested for abusing her girlfriend at the time but her girlfriend denied it or something when questioned by the police and they both accused the policeman of being homophobic and that being the reason why he accused her of such a thing.But the policeman turned out to be gay himself,so...',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       "Amber Heard does not have a history of accusing people of domestic violence and her ex-wife has never accused her of anything either.  \n\nBut for what it's worth, some relationships can bring out a dark side in you. Not having a pattern of physical violence isn't necessarily an indication that someone doesn't have the capacity to be violent, given the right triggers. Also, people like to romanticise Johnny Depp because when most of us were kids and adolescents, he was fun and cheeky Jack Sparrow and a devoted family man. But in his 20s he was a bit of a hellraiser, a heavy drinker with a temper and a destructive streak. \n\nPersonally I think it was a toxic relationship that became violent due to heavy alcohol and perhaps drug abuse, and that it could have gone both ways. ",
       'NEWS:Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows [r/movies by u/JediBurrell]',
       'Original post: [Johnny Depp was abused by ex-wife Amber Heard, new evidence shows](/r/movies/comments/b1bdis/johnny_depp_was_abused_by_exwife_amber_heard_new/)',
       "If only not [one](https://www.tmz.com/2016/05/29/johnny-depp-ex-partner-wife-amber-heard-vanessa/) but [two](https://www.tmz.com/2016/05/28/johnny-depp-ex-wife-denies-abuse/) of his exes, or even [one](https://www.thewrap.com/johnny-depp-is-being-blackmailed-by-amber-heard-heres-how-i-know-guest-column/) of his friends, had defended him two years ago or let people know that he was the one being abused, maybe he wouldn't have been torn apart by the media and general public.",
       '[#1|+8294|1192] Johnny Depp was abused by ex-wife Amber Heard, new evidence shows [/r/movies]',
       'This is being censored by the default subs - Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'I’ve been saying this all along, I had a female abuser and that video Heard posted is exaclty the kind of fake displays my ex would use to deflect. Heard’s behavior during and after their divorce never made sense. Also she has a record of domestic abuse toward her ex-wife. Depp’s ex’s all came forward and said it was incredibly out of character. \n\nEdit: Thank you so much for the gold generous fellow Redditor! I hope the truth is finally revealed in this case. \nSolidarity to all domestic abuse survivors whether male or female. \n\n2nd Edit: Thank you generous fellow redditor for the Silver! Some of us have female abusers, good to acknowledge each other even if anonymously. ',
       "I remember his ex wife came out to defend him when it was announced. \n\n> Lori - who spoke to the actor last week following the death of his mother - has told friends Johnny never got physical with her during their relationship and did not even scream at her in anger.\n\n>Lori - who remains friends with Johnny - dubbed the Pirates Of The Caribbean star a 'soft person'.\n\nEdit: I found the article\n\nhttps://www.dailymail.co.uk/tvshowbiz/article-3614450/Johnny-Depp-s-ex-wife-Lori-Anne-Allison-claims-never-lay-hand-woman-actor-accused-abusing-Amber-Heard.html",
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows [Relevancy in Comments]',
       '"abused ex wife" - according to said ex wife. You post that drivel in here - in this thread - where the problem is a one-sided accusation from an ex-wife that turned out to be blatantly false? And people upvote you? They never learn.',
       "'New photos and evidence were released to the public on Tuesday revealing actor Johnny Depp was abused by his ex-wife Amber Heard.'\n\nSo where are the pictures for F's sake? If they were released to the public, why didn't they at least link them?",
       'She had an ex-wife who confirmed she is manipulative and abusive, while every single character witness for Depp says he’s never abused anyone in any way in his entire life.\n\nShe’s a fraud, and she’s manipulating you too based on your solidarity urge to relate to other women. ',
       '[Mods deleted the previous one] Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard new evidence shows.',
       '> She admitted to the abuse. The article state that. It\'s validated by the court report. \n\nI honestly cannot find that in the article. Can you please quote it?\n\nEdit 2: i couldn’t find it, because it wasn’t in the article or was “mysteriously edited out” to prevent plagiarism or whatever bullshit thats being claimed\n\nEdit:\n\nThe entire article:\n\n> New photos and evidence were released to the public on Tuesday revealing actor Johnny Depp was abused by his ex-wife Amber Heard.\nThe latest evidence came to light as Depp sued Heard for $50 million for defamation. The case has shown that Heard has in fact admitted to the abuse while being under oath.\nHeard had alleged that the Pirates of the Caribbean actor had physically abused her during their marriage. The couple separated in 2016, when she filed for divorce and accused him of physically abusing her, but now he has filed a lawsuit against her, in which he alleges she punched him in the face and chopped off his finger.\nThe new pictures released show Depp’s face with a huge black bruise, and a haunting photo of his finger, half chopped off.\nDepp also submitted 87 surveillance camera videos to the court, 17 depositions of witnesses (which includes police officers), and the images.\n“Ms. Heard is not a victim of domestic abuse, she is a perpetrator,” the lawsuit says in reaction to Amber Heard penning an op-ed in The Washington Post back in 2018, which the lawsuit further says is nothing more than an "elaborate hoax," and that she also used those claims to further her career in the wake of the #MeToo movement.\n“They were part of an elaborate hoax to generate positive publicity for Ms Heard and advance her career,” the lawsuit says of the allegations against Depp’s violent behaviour, which his lawyers claim is the reason he is no longer a part of Disney\'s Pirates of The Caribbean franchise and reboot.\nThe lawsuit alleges incidents where Heard thew a bottle of vodka at Depp, which resulted in an injury to his hand requiring surgery, punching Depp as he was in bed, kicking him on numerous occasions, and even staging her own attacks.\n"Unaware that members of Mr Depp\'s security team (including an 18-year veteran of the Los Angeles County Sheriff’s Department) were mere feet away, Ms Heard falsely began yelling, \'Stop hitting me, Johnny,\'" the lawsuit states. "The interaction culminated with Ms Heard making false allegations that Mr Depp struck her with a cell phone, hit her and destroyed the penthouse. There were multiple eyewitnesses to this hoax."\nThere has been an outpouring of support for the actor with many apologising over social media for accusing him of abuse.',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'My ex-husband with BPD punched himself in the eye and told everyone I did it. He stabbed himself in the hand with a fork when he attempted to stab the flip phone he was holding, and told everyone that his mom who was on the other end of the call did it.\n\nThankfully everyone he told had already been a victim of him claiming to be their victim. (His mom tried to kill him by leaving him in a hot car when he was 10, his sister sexually abused him, he was harassed by his ex-wife, his dad sexually assaulted him, his best friend cursed him with a magic hex...)',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp, accused of spousal abuse, was abused by ex-wife Amber Heard',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows • r/MGTOW',
       '> "Amber Heard definitely lied about everything in that relationship. Dude bent over backward for her, including doing some dumb shit, trying to get her dogs into Australia without following immigration procedures. That bitch is a sociopath - **for years [she was a lesbian](http://archive.fo/n2L3z#selection-2467.0-2479.30), then suddenly she is marrying a dude, and she has no real body of work. This was a career maneuver for her, pure and simple.**" —[ForensicatingEdibles](https://www.reddit.com/r/pussypassdenied/comments/awvaeh/johnny_depp_files_50_million_defamation_lawsuit/ehpjilt/)\n\nNumerous articles have come out on this one on Reddit ([1](https://www.reddit.com/r/MGTOW/comments/b10u79/just_more_truths_for_my_fellow_mgtows/), [2](https://www.reddit.com/r/MGTOW/comments/b1k7oz/johnny_depp_was_abused_by_exwife_amber_heard_new/), [3](https://www.reddit.com/r/pussypassdenied/comments/awvaeh/johnny_depp_files_50_million_defamation_lawsuit/), [4](https://www.reddit.com/r/MGTOW/comments/b1f1uf/wow/)) and elsewhere.\n\n1. [**Globalnews.ca**: Johnny Depp claims Amber Heard punched him ‘twice in the face’](https://globalnews.ca/news/4367197/johnny-depp-amber-heard-punched-him/)\n2. [**Geo.tv**: Johnny Depp was abused by ex-wife Amber Heard, new evidence shows](https://www.geo.tv/latest/230905)\n3. [**DailyWire**: People Believed Johnny Depp Was A Domestic Abuser. It Turns Out He May Have Been The Victim.](https://www.dailywire.com/news/44616/people-believed-johnny-depp-was-domestic-abuser-it-ashe-schow)\n4. [**Twitter**: Fake bruise on Amber Heard](https://twitter.com/Zoe_Heriot_/status/1104363876576047105)\n5. [**Jakarta Post**: The Amber Heard-Johnny Depp domestic abuse case just got even messier](https://www.thejakartapost.com/life/2019/03/14/the-amber-heard-johnny-depp-domestic-abuse-case-just-got-even-messier-.html)',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, who accused him of sexual assault to further her career',
       'Johnny Depp sues ex-wife Amber Heard for $50million over abuse claims',
       '>Johnny Depp has claimed that he has submitted 87 surveillance videos to support his defamation case against his ex-wife Amber Heard.\n\nWhy now? Why did he not release this sooner? ',
       'Johnny Depp files counter-lawsuit against Amber Heard, accuses ex-wife of domestic abuse. ~ Based on this news, I think it sheds light on the contentious relationship Elon had with Heard.',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows | Entertainment - Geo.tv (/r/WeinsteinEffect)',
       'Johnny Depp accuses ex-wife Amber Heard of abuse, chopping his finger',
       'Johnny Depp was abused by ex-wife Amber Heard, new evidence shows',
       '> New photos and evidence were released to the public on Tuesday revealing actor Johnny Depp was abused by his ex-wife Amber Heard.\n\nOk, where are they?',
       "Johnny Depp's ex-wife, Amber Heard, asks judge to dismiss $50M defamation lawsuit",
       "[Entertainment] - Johnny Depp's ex-wife, Amber Heard, asks judge to dismiss $50M defamation lawsuit",
       "[Entertainment] - Johnny Depp's ex-wife, Amber Heard, asks judge to dismiss $50M defamation lawsuit | USA Today",
       'Johnny Depp is reportedly dragging Elon Musk into the bitter legal fight with his ex-wife Amber Heard - INSIDER',
       "Johnny Depp accuses ex-wife Amber Heard of 'painting-on' bruises",
       "[World] - Johnny Depp accuses ex-wife Amber Heard of 'painting-on' bruises",
       "Johnny Depp accuses ex-wife Amber Heard of 'painting-on' bruises",
       "Johnny Depp accuses ex-wife Amber Heard of 'painting-on' bruises",
       "[World] - Johnny Depp accuses ex-wife Amber Heard of 'painting-on' bruises | Guardian",
       'Johnny Depp claims ex-wife Amber Heard defecated on his bed, says that’s when he resolved to divorce her',
       "Johnny Depp accuses ex-wife Amber Heard of 'painting-on' bruises",
       "He's already suing.  That is why there are loads of articles.  The first paragraph of the article we are discussion literally says this.\n\n>Johnny Depp is accusing his ex-wife Amber Heard of abusing him in his first declaration as part of his $50 million defamation lawsuit against her.\n\nSeriously?",
       "'I was the victim': Johnny Depp says ex-wife Amber Heard 'painted on' bruises, report claims",
       "'I was the victim': Johnny Depp says ex-wife Amber Heard 'painted on' bruises, report claims",
       '‘I was the victim’: Johnny Depp says ex-wife Amber Heard ‘painted on’ bruises, report claims',
       '‘I was the victim’: Johnny Depp says ex-wife Amber Heard ‘painted on’ bruises, report claims',
       'Johnny Depp claims ex-wife Amber Heard defecated on his bed, says that’s when he resolved to divorce her',
       'Johnny Depp claims ex-wife Amber Heard defecated on his bed, says that’s when he resolved to divorce her',
       'Johnny Depp blames ex-wife Amber Heard for a cut off finger, in “his career struggle”: “Her bruises were make-up”',
       'Well she claimed that he would have beaten her. She even went to court. Interesting case since the police came and did not see anything on her. His ex-wife vanessa paradis and their daughter jumped to his side, telling the press that he never got violent against them and they couldn‘t imagine he‘d ever will attack woman.  She won at court anyway, but during this time she tried to look good by declaring that she would give all the money to charity.   \nI don‘t know Johny in person, but i know drunks, some attack people, some can and will direct their anger NOT on people. I think, he is one of them. No proof, just gut feeling and the vows of exwife and daughter.  \n  \nAfter that see was seen with Elon Musk for a short time, but that guy seems smart. And i forgot: SHE has a history of violence. so...',
       "[Arts] - James Franco subpoenaed in Johnny Depp's $50 million lawsuit against ex-wife Amber Heard",
       "[Arts] - James Franco subpoenaed in Johnny Depp's $50 million lawsuit against ex-wife Amber Heard | The Independent",
       "Johnny Depp's ex-wife.  She accused him of being abusive, but evidence eventually came to light suggesting that she was the more abusive one in the relationship.",
       'I don\'t know what this subject is doing in this sub. It\'s to suggest that "women as chaos"? Because if in case it is the intention of the thread, I would like to remember that such abusive attitude is not exclusive to women. It\'s just an other case of a human being trying to take money from an other human being without have to look for a job. Remember that it was his ex-wife who defended JD in court and online.',
       'His ex-wife has only ever said good things about him as far as I know, so I am definitely skeptical.',
       '"Johnny Depp has claimed that he has submitted 87 surveillance videos to support his defamation case against his ex-wife Amber Heard". \n\nhttp://www.ladbible.com/entertainment/news-johnny-depp-submits-87-videos-of-amber-heard-attacking-him-to-court-20190316',
       'Also saw that Depp’s other ex-wife (who I didn’t even know existed) also supports Depp',
       'New accusations of Johnny Depp to his ex-wife Amber Heard: “She put out my cigarette on my cheek”',
       'yeah his ex-wife and daughter said they never experienced Depp the way Heard claimed. Personally I think Heard was looking for some press to get her name out there, she definitely seems the type of person who would do that.',
       'https://mobile.twitter.com/cinemapatti/status/1105438073423159296?ref_url=https%3a%2f%2fwww.5why.com.au%2fchilling-new-evidence-shows-johnny-depp-was-violently-abused-by-amber-heard%2f\n\nThe photo of the finger is NSFW, maybe NSFL. \n\nI don’t know if I have to flag that somehow, but it had to be mentioned.\n\nAdditional article: https://www.geo.tv/latest/230905-johnny-depp-was-abused-by-ex-wife-amber-heard-new-evidence-shows\n\n“The case has shown that Heard has in fact admitted to the abuse while being under oath.”',
       'It’s still ongoing. Here’s a timeline:\n\nhttps://www.eonline.com/news/1054235/a-complete-timeline-of-johnny-depp-and-amber-heard-s-ongoing-legal-battle\n\nAs far as I’m aware, it’s still ongoing and will be for a while. \n\nBut all the evidence I’ve seen points toward Heard lying. These things don’t just happen - they’re a pattern. They escalate. This marriage was two years long and [heard has a history of abuse.](https://www.latimes.com/entertainment/gossip/la-et-mg-amber-heard-girlfriend-domestic-violence-20160607-snap-story.html) it’s pretty open-and-shut IMO.\n\n[Even his first ex-wife says as much, and she was married to him longer. ](https://www.tmz.com/2016/05/28/johnny-depp-ex-wife-denies-abuse/) \n\nAll of that plus the witness testimony and the photo of the finger (initially released when he was In the hospital - happened while he and heard were married) add up to heard lying.',
       'Heard was *arrested for misdemeanor assault* and then the charges were dropped.\n\nhttps://www.usatoday.com/story/life/movies/2016/06/07/amber-heard-arrested-2009-charge-hitting-girlfriend/85563338/\n\nJust because you decide not to press charges and decide to have the arrest wiped from records and then decide to defend someone arrested for misdemeanor assault doesn’t mean they didn’t commit misdemeanor assault. Hell, the current president’s ex-wife testified under oath that he raped her, then turned around and claimed that was a lie - I’m not saying that’s what happened, but that it happens all the time, and ignoring a literal arrest for assault is a little unfair. If Depp had a similar arrest I’d be saying the same thing. \n\nThis article says that he hurt himself while fighting on the phone with heard:\n\nhttps://www.dailymail.co.uk/news/article-3741910/Photo-Johnny-Depp-s-ghastly-finger-cut-tip-fit-rage-wrote-blood-wall-Amber-Heard-affair-Billy-Bob-Thornton.html\n\nSo I’m beginning to wonder if the whole finger issue is irrelevant (unless there was verbal abuse over the phone, which I’m not seeing there being any claims of). He clearly hurt himself and blamed his reaction on her. Even if he’s innocent, he’s an idiot on this one. \n\nI understand that a lawsuit isn’t a ruling, but that doesn’t mean that multiple eyewitnesses should be discounted, either. \n\nIt’s certainly true that you can abuse nobody your entire life and then abuse someone else terribly. I’m not saying otherwise - all I’m saying is that a character witness such as an ex-wife should certainly have weight to it when compared to someone with a history of assault. \n\nBrock turner is a piece of shit - but the testimony (‘written letter’ - not even testimony) of a girlfriend at 17-18 in high school is different from an ex-wife of three years in many different ways. While I agree with your point, I think this specific comparison is a little unfair as there weren’t any sexual assault claims that I know of. \n\nWe’re all entitled to our opinions, and obviously neither of us are going to change ours with the information that’s been released to the public. Clearly they’re both trying to control the narrative, and it goes without saying that neither of their lawyers’ other clients inspire confidence. I, too, will wait for a final verdict in all of this. (I’m friends with some people in depp’s professional circle and it’s made me a little partial for obvious reasons)',
       'I don’t think this particular reply was necessary, my friend. I tried to come to a reasonable middle ground here, but you seem to be pretty adamant about dismissing relevant information. An arrest for assault is an arrest for assault. Yeah, cops don’t determine guilt. Yeah, you can dispute those things and be correct. But you seem to think that a victim (particularly one less famous and rich than the alleged abuser) couldn’t be coerced into saying something didn’t happen after an arrest was made? That’s why I made the trump comparison (and immediately afterwards said that I wasn’t saying that was what happened in this situation, but rather used it as an example that people can be assaulted and coerced into saying it wasn’t true).\n\nWould you find yourself in a situation that looks to a police officer like you assaulted someone? I mean, I’m pretty damned sure that nothing I’ve ever done would look like assault to an officer, and can’t think of anything someone would do that would look like assault to a cop but wasn’t. Again, I could very well be wrong about it. But the arrest for assault... is relevant information in a case about assault, man, despite you wanting it not to be. If Depp were in the same boat, I’d say the same about him. \n\nLol... Brock turner clearly raping several teens (edit: convicted of 3 assault charges, not against different people. I got that wrong.) and Depp saying he was the subject of abuse rather than an abuser while providing evidence of such is **vastly different**. Kind of horrible of you to continue pushing this narrative. Anyone can be a physical abuser, anyone can be a rapist - but multiple accusations of rape against one person point to a pattern while one incident that appears (like it or not) to be either mutual abuse or fabricated abuse on one side is NOT the same. Period. \n\nI, twice, agreed that no past abuse does not imply a lack of present abuse. Here I am doing it a third time. Weird how you chose to pretend I didn’t. \n\nAnd lastly, this affects my professional circle, so yeah I will naturally look for innocence in the people I’m more familiar with - and me acknowledging as much and learning along the way is all I can do in response. It must be nice to not care about this - my career path might just completely change because of this. \n\nYou can claim my arguments are poorly sourced, but I clearly know what I’m talking about (I looked for and provided you court filings, while you sent me daily mail links. C’mon.) and very obviously conceded where I learned my research was lacking. You’re the only one here digging in your heels. \nDon’t be a dick about it.\n\nEdit: Brock Turner was convicted on three felony counts of assault. I, for whatever reason, assumed that meant three victims, and assumed they were 18 or 19 instead of being one 22 year old. That certainly doesn’t make me a liar, and certainly doesn’t disprove my point that ONE person imprisoned on THREE COUNTS OF ASSAULT (rape) is VASTLY different from TWO PEOPLE each claiming the other person abused them and each providing evidence against the other. Nobody accused anybody of rape, they were married and Turner wasn’t (a vastly different relationship), and an ex-wife of three years defending her ex-husband has a shitton more bearing (in my mind) than a 17 year old girl who said that a then-18-year-old-boy was nice to her in high school.'],
      dtype=object)


with pd.option_context('display.max_colwidth', None):
  display(df_her.head())


text = "Amber Heard in Aquaman 2, why?"

df_aqua = df[df.text.str.contains(text)]
df_aqua = df_aqua.sort_values('created_at')

print(df_aqua.shape)
df_aqua.head() 

# .style.applymap(lambda x: helpers.coloring(x, {'Positive': '#deebce', 'Negative': '#edbcbb'}),
# subset=['sentiment_blob', 'sentiment_nltk'])

(0, 17)


text = "What did she hear?".lower()

df_hear = df[df.text.str.contains(text)]
# df_her = df_her.sort_values('created_at')

print(df_hear.shape)
df_hear.head()

(3, 17)


df_hear.author.value_counts()

mattreyu          1
-TheExtraMile-    1
cuacuacuac        1
Name: author, dtype: int64


df_hear.subreddit.value_counts()

r/celebnsfw     1
r/geekboners    1
r/goddesses     1
Name: subreddit, dtype: int64


df_hear.top_level.value_counts()

submission    3
Name: top_level, dtype: int64


df_hear.submission_comment.value_counts()

comment    3
Name: submission_comment, dtype: int64


df['text_words'].value_counts().head(10);


px.histogram(df['text_words'].to_frame(), x="text_words",title='number of words in each contribution',
            nbins=200).update_traces(marker_color='#5296dd')


px.bar(data_frame=df['top_level'].value_counts().to_frame().reset_index(),
       x="index", y="top_level", text="top_level").update_layout(title='Comment or Submission (Top Level of Contrbution "Parent")',
                   xaxis_title='contribution top level (parent) category',
                   yaxis_title='number of contributions').update_traces(marker_color='#5296dd')


df['submission_text'].value_counts().head(10)

johnny_depp_was_abused_by_exwife_amber_heard_new    4958
amber_heard                                         4308
DC_Cinematic                                         784
johnny_depp_files_50_million_defamation_lawsuit      652
report_james_marsden_amber_heard_in_negotiations     469
the_naked_truth_about_johnny_depp_case_and_what      417
johnny_depps_50m_defamation_suit_against_amber       401
johnny_depp_fans_are_pushing_hard_to_get_amber       319
johnny_depp_files_new_legal_docs_claiming_proof      293
petition_to_remove_accused_dv_perpetrator_amber      282
Name: submission_text, dtype: int64


df_mera = df.query(" submission_text == 'johnny_depp_was_abused_by_exwife_amber_heard_new' & \
                           submission_comment == 'submission' ")
print(df_mera.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_mera.head())

(34, 17)


li = list(df_mera.author.unique())
li.remove('-banned-')
df_users[df_users.user_name.isin(li)]


df_mera_comments = df.query(" submission_text == 'johnny_depp_was_abused_by_exwife_amber_heard_new' ")
print(df_mera_comments.shape)
df_mera_comments.head(1)

(4958, 17)


df_mera_contributions = df_mera_comments.groupby(df_mera_comments.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_contributions.head(7),
             x='created_at', 
             y='n_contributions', title='The number of contributions/date on these submissions')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_mera_contributions.head(7).created_at,
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_mera_contributions.n_contributions] 

fig.update_traces(marker_color=clrs, marker_line_width=1.5, opacity=1, textposition='auto')

fig.show()


df_mera_authors = df_mera_comments.groupby(df_mera_comments.author).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_authors,
             x='author', 
             y='n_contributions', title='The number of contributions per author on these submissions')
fig.update_traces(opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,25])

fig.show()


df_mera_authors.sort_values('n_contributions', ascending=False).head(10)


df_users.query(" user_name in ['guac_boi1', 'Pixelated_Piracy', 'majortom106']")


df_mera = df.query(" submission_text == 'amber_heard' & \
                           submission_comment == 'submission' ")
print(df_mera.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_mera.head())

(1717, 17)


li = list(df_mera.author.unique())
li.remove('-banned-')
df_users[df_users.user_name.isin(li)]


df_mera_comments = df.query(" submission_text == 'amber_heard' ")
print(df_mera_comments.shape)
df_mera_comments.head(1)

(4308, 17)


df_mera_contributions = df_mera_comments.groupby(df_mera_comments.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_contributions.head(7),
             x='created_at', 
             y='n_contributions', title='The number of contributions/date on these submissions')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_mera_contributions.head(7).created_at,
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_mera_contributions.n_contributions] 

fig.update_traces(marker_color=clrs, marker_line_width=1.5, opacity=1, textposition='auto')

fig.show()


df_mera_authors = df_mera_comments.groupby(df_mera_comments.author).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_authors,
             x='author', 
             y='n_contributions', title='The number of contributions per author on these submissions')
fig.update_traces( opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,25])

fig.show()


df_mera_authors.sort_values('n_contributions', ascending=False).head(10)


df_users.query(" user_name in ['AutoModerator', 'Dannig178', 'RuleIV']")


df_mera = df.query(" submission_text == 'johnny_depp_files_50_million_defamation_lawsuit' & \
                           submission_comment == 'submission' ")
print(df_mera.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_mera.head())

(10, 17)


li = list(df_mera.author.unique())
li.remove('-banned-')
df_users[df_users.user_name.isin(li)]


df_mera_comments = df.query(" submission_text == 'johnny_depp_files_50_million_defamation_lawsuit' ")
print(df_mera_comments.shape)
df_mera_comments.head(1)

(652, 17)


df_mera_contributions = df_mera_comments.groupby(df_mera_comments.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_contributions.head(7),
             x='created_at', 
             y='n_contributions', title='The number of contributions/date on these submissions')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_mera_contributions.head(7).created_at,
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_mera_contributions.n_contributions] 

fig.update_traces(marker_color=clrs, marker_line_width=1.5, opacity=1, textposition='auto')

fig.show()


df_mera_authors = df_mera_comments.groupby(df_mera_comments.author).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_authors,
             x='author', 
             y='n_contributions', title='The number of contributions per author on these submissions')
fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,25])

fig.show()


df_mera_authors.sort_values('n_contributions', ascending=False).head(10)


df_users.query(" user_name in ['armoured_bobandi', 'masksnjunk', 'Doctah__Wahwee']")


df_mera = df.query(" submission_text == 'report_james_marsden_amber_heard_in_negotiations' & \
                           submission_comment == 'submission' ")
print(df_mera.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_mera.head())

(2, 17)


li = list(df_mera.author.unique())
df_users[df_users.user_name.isin(li)]


df_mera_comments = df.query(" submission_text == 'report_james_marsden_amber_heard_in_negotiations' ")
print(df_mera_comments.shape)
df_mera_comments.head(1)

(469, 17)


df_mera_contributions = df_mera_comments.groupby(df_mera_comments.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_contributions.head(7),
             x='created_at', 
             y='n_contributions', title='The number of contributions/date on these submissions')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_mera_contributions.head(7).created_at,
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_mera_contributions.n_contributions] 

fig.update_traces(marker_color=clrs, marker_line_width=1.5, opacity=1, textposition='auto')

fig.show()


df_mera_authors = df_mera_comments.groupby(df_mera_comments.author).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_authors,
             x='author', 
             y='n_contributions', title='The number of contributions per author on these submissions')
fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,25])

fig.show()


df_mera_authors.sort_values('n_contributions', ascending=False).head(10)


df_users.query(" user_name in ['sweetestdeth', 'paperbackgarbage', 'col-fancypants']")


df_mera = df.query(" submission_text == 'the_naked_truth_about_johnny_depp_case_and_what' & \
                           submission_comment == 'submission' ")
print(df_mera.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_mera.head())

(2, 17)


li = list(df_mera.author.unique())
df_users[df_users.user_name.isin(li)]


df_mera_comments = df.query(" submission_text == 'the_naked_truth_about_johnny_depp_case_and_what' ")
print(df_mera_comments.shape)
df_mera_comments.head(1)

(417, 17)


df_mera_contributions = df_mera_comments.groupby(df_mera_comments.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_contributions.head(7),
             x='created_at', 
             y='n_contributions', title='The number of contributions/date on these submissions')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_mera_contributions.head(7).created_at,
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_mera_contributions.n_contributions] 

fig.update_traces(marker_color=clrs, marker_line_width=1.5, opacity=1, textposition='auto')

fig.show()


df_mera_authors = df_mera_comments.groupby(df_mera_comments.author).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_authors,
             x='author', 
             y='n_contributions', title='The number of contributions per author on these submissions')
fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,25])

fig.show()


df_mera_authors.sort_values('n_contributions', ascending=False).head(10)


df_users.query(" user_name in ['Lily_Roza']")


df_mera = df.query(" submission_text == 'petition_to_remove_accused_dv_perpetrator_amber' & \
                           submission_comment == 'submission' ")
print(df_mera.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_mera.head())

(4, 17)


li = list(df_mera.author.unique())
li.remove('-banned-')
df_users[df_users.user_name.isin(li)]


df_mera_comments = df.query(" submission_text == 'petition_to_remove_accused_dv_perpetrator_amber' ")
print(df_mera_comments.shape)
df_mera_comments.head(1)

(282, 17)


df_mera_contributions = df_mera_comments.groupby(df_mera_comments.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_contributions.head(7),
             x='created_at', 
             y='n_contributions', title='The number of contributions/date on these submissions')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_mera_contributions.head(7).created_at,
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_mera_contributions.n_contributions] 

fig.update_traces(marker_color=clrs, marker_line_width=1.5, opacity=1, textposition='auto')

fig.show()


df_mera_authors = df_mera_comments.groupby(df_mera_comments.author).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_authors,
             x='author', 
             y='n_contributions', title='The number of contributions per author on these submissions')
fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,25])

fig.show()


df_mera_authors.sort_values('n_contributions', ascending=False).head(10)


df_users.query(" user_name in ['ThePigmanAgain', 'Gingerchaun', '5th_Law_of_Robotics']")


df.parent_id.value_counts().head()

t3_b1bdis    273
t3_b1ccsj    253
t3_b10ld3    147
t3_bn6sot    145
t3_ako0za    142
Name: parent_id, dtype: int64


fig = px.bar(df.parent_id.value_counts().to_frame().head(25).reset_index(), x="parent_id", y="index",
             height=500,
             title='sumbissions with most comments (Top Level Comments)').update_layout(
                   xaxis_title='Number of comments',
                   yaxis_title='subbredit').update_traces(marker_color='#5296dd')

fig.update_yaxes(autorange="reversed")


df_top5 = df_merged[df_merged.child_id.isin(df_merged.parent_id.value_counts().head().index)]

with pd.option_context('display.max_colwidth', None):
  display(df_top5)


df_merged.submission_text = df_merged.submission_text.str.replace('_', ' ')


# get a list with the top 5 submission text
top5_text = list(df_top5.text)


def compare(str):
    for text in top5_text:
        if str in text:
            return True
        else: return False


mask = df_merged.submission_text.apply(compare)

df_top5_contributions1 = df_merged[mask]

df_top5_authors = df_top5_contributions1.groupby(df_top5_contributions1.user_name).size().reset_index(name='n_contributions')

fig = px.bar(df_top5_authors,
             x='user_name', 
             y='n_contributions', title='The number comments per author on these submissions')

fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 

fig.show()


df_top5_contributions1.shape

(34, 24)


df_top5_contributions2 = df_merged[df_merged.parent_id.isin(df_merged.parent_id.value_counts().head().index)]

df_top5_authors = df_top5_contributions2.groupby(df_top5_contributions2.user_name).size().reset_index(name='n_contributions')


fig = px.bar(df_top5_authors,
             x='user_name', 
             y='n_contributions', title='The number of parent comments per author on these submissions')
fig.update_traces( opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,5])

fig.show()


df_top5_authors.sort_values('n_contributions', ascending = False)


str(round(137 / df_top5_contributions2.shape[0] * 100, 2)) + ' % of contributions made by banned users'

'14.27 % of contributions made by banned users'


df_submissions = df[df.submission_comment == 'submission']
print(df_submissions.shape)
df_submissions.head(2)

(3818, 17)


df_submissions.author.value_counts().nlargest(n=10)

-banned-              1294
spells010               80
Dannig178               67
newsfeedmedia           62
Sovetika                48
AutoNewsAdmin           36
AutoNewspaperAdmin      34
DerHander               30
bitcoinwallpaper2       30
InfiniTitans            28
Name: author, dtype: int64


df_submissions.author.value_counts().to_frame().head(10)


fig = px.bar(df_submissions.author.value_counts().to_frame().head(10).reset_index(), x="author", y="index",
             height=500,
             title='Authors with most Submissions').update_traces(marker_color='#5296dd',).update_layout(
                   xaxis_title='Number of Negative Submissions',
                   yaxis_title='Author_Name').update_traces(marker_color='#5296dd')

fig.update_yaxes(autorange="reversed")


df_submissions.author.value_counts().head()

-banned-         1294
spells010          80
Dannig178          67
newsfeedmedia      62
Sovetika           48
Name: author, dtype: int64


check_list = df_submissions.author.value_counts().nlargest(n=25).index.tolist()[1:]
check_list

['spells010',
 'Dannig178',
 'newsfeedmedia',
 'Sovetika',
 'AutoNewsAdmin',
 'AutoNewspaperAdmin',
 'DerHander',
 'bitcoinwallpaper2',
 'InfiniTitans',
 'Rednaxela117',
 'jwmonty8889',
 'GRJR721',
 'Eagles1205',
 'amigokomashiangeljr',
 'Queen1110',
 'imsrikant',
 'MuskieFan18',
 'FreedomNewsPolitics',
 'LightUpStreets',
 'emilyguy',
 '-en-',
 'iDevice_Help',
 'LongClawww',
 '88MPH1']


# get a data frame with the most negative-comments users
df_check = df_users[df_users['user_name'].isin(check_list)]
print(df_check.shape)
df_check.head(2)

(24, 10)


df_check['user_name'].nunique()

24


get_stats(df_check)

The value counts of the users with the most contributions: has_verified_email
True     23
False     1
Name: has_verified_email, dtype: int64


The value counts of the users with the most contributions: is_mod
True     19
False     5
Name: is_mod, dtype: int64


The value counts of the users with the most contributions: is_gold
False    17
True      7
Name: is_gold, dtype: int64


The value counts of the users with the most contributions: is_banned
False    19
True      5
Name: is_banned, dtype: int64


The min of comment_karma 0.0


The max of comment_karma 26585.0


The mean of comment_karma 4481.74


The median of comment_karma 4481.74


The min of link_karma 1.0


The max of link_karma 1836704.0


The mean of link_karma 263380.79


The median of link_karma 263380.79


The value counts of the users with the most contributions: banned_unverified
others        18
banned         5
unverified     1
Name: banned_unverified, dtype: int64


The value counts of the users with the most contributions: creation_year
others    12
banned     5
2018       5
2019       2
Name: creation_year, dtype: int64


df['urls'].nunique()

309


df[df.astype(str)['urls'] != '[]'].head(2)


df['urls'].astype('str').value_counts().head()

[]                                                                                    22608
['https://jerkofftocelebs.com', 'https://www.instagram.com', 'https://discord.gg']       94
['https://www.instagram.com']                                                            88
['https://www.instagram.com', 'https://discord.gg']                                      64
['https://www.reddit.com']                                                               63
Name: urls, dtype: int64


# the value counts of the # of urls
df['urls_count'].value_counts();


fig = px.histogram(df['urls_count'].to_frame(), x="urls_count",title='Count of the number of URLS in each Contribution',
            nbins=130).update_traces(marker_color='#5296dd')

fig.update_layout(
    xaxis = dict(
        tickmode = 'array',
        tickvals = df['urls_count'],
    )
)

fig.show()


px.histogram(df[~(df['urls_count'].isin([0,60,20,16]))], x="urls_count",title='Count of the number of URLS in each Contribution',
            nbins=20).update_traces(marker_color='#5296dd')


fig = px.histogram(df['submission_words'].to_frame(), x="submission_words",
                   title='number of words in submission text',
                   nbins=50).update_traces(marker_color='#5296dd')

fig.update_layout(
    xaxis = dict(
        title='Number of submission words',
        tickmode = 'linear',
    )
)


df['subreddit'].nunique()

535


df['subreddit'] = df['subreddit'].str[:]


df.subreddit.value_counts().to_frame().head(10)


fig = px.bar(df.subreddit.value_counts().to_frame().head(20).reset_index(), x="subreddit", y="index",
             height=500,
             title='Most used subbredits').update_traces(marker_color='#5296dd',).update_layout(
                   xaxis_title='Number of comments',
                   yaxis_title='subbredit').update_traces(marker_color='#5296dd')

fig.update_yaxes(autorange="reversed")


# note that value_counts() neglect Zeros
df_merged["days_after_creation"].value_counts()

2685.0    508
2684.0    297
2683.0    186
2686.0    179
2.0       104
         ... 
3060.0      1
2363.0      1
2175.0      1
1571.0      1
3266.0      1
Name: days_after_creation, Length: 3291, dtype: int64


px.histogram(df_merged, x="days_after_creation",title='days_after_creation',
            nbins=250).update_traces(marker_color='#5296dd',).update_layout(
                   xaxis_title='number of days',)


print('The number of accounts posted the same day they was created!', df_merged[df_merged['days_after_creation'] == 0].shape[0])

The number of accounts posted the same day they was created! 66


print('The number of accounts posted the same week they was created', df_merged[df_merged['days_after_creation'] <= 7].shape[0])

The number of accounts posted the same week they was created 307


print('The number of accounts posted the same month they was created', df_merged[df_merged['days_after_creation'] <= 30].shape[0])

The number of accounts posted the same month they was created 734


df_merged[df_merged['days_after_creation'] <= 30]['user_created_at'].dt.year.value_counts()

2019    712
2018     22
Name: user_created_at, dtype: int64


mask = (df_merged['days_after_creation'] <= 30) & (df_merged['user_created_at'].dt.year == 2019)
df_merged[mask]['user_created_at'].dt.strftime('%b').value_counts()

Feb    130
Jul    125
Mar    115
Oct     74
May     52
Jun     42
Jan     40
Apr     35
Sep     34
Aug     29
Nov     23
Dec     13
Name: user_created_at, dtype: int64


months = df_merged[df_merged['days_after_creation'] <= 30]['user_created_at'].dt.strftime('%b')
months

4532     Dec
4567     Dec
4583     Dec
5068     Dec
5069     Dec
        ... 
23662    Dec
23663    Dec
23664    Dec
23668    Dec
23669    Dec
Name: user_created_at, Length: 734, dtype: object


months_sorted = months.value_counts()


months_sorted

Feb    130
Jul    125
Mar    115
Oct     74
May     52
Jun     42
Jan     40
Apr     35
Dec     35
Sep     34
Aug     29
Nov     23
Name: user_created_at, dtype: int64


new_order = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']


months_sorted = months_sorted.reindex(new_order, axis=0)


months_sorted.to_frame().reset_index().rename(columns={'index':'month'})


fig = px.bar(months_sorted.to_frame().reset_index().rename(columns={'index':'month'}),
             x='month', y='user_created_at', text='user_created_at')

fig.update_layout(
            title={
        'text': "contributions of the accounts posted/commented <br> the same month they were created",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

# fig.update_layout(
#     xaxis = dict(
#         title='Month(2021)',
#         tickmode = 'array',
#         tickvals = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
#         ticktext = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
#         )
# )

clrs = ['red' if (y > 100) else '#5296dd' for y in months_sorted.values] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


# THE SAME MONTH:
# check for the date these accounts posted/commented 
reddit_30 = df_merged[df_merged['days_after_creation'] <= 30]

dates_count = df_merged.groupby(reddit_30['created_at'].dt.date).size().reset_index(name='contributions')
dates_count.sort_values('contributions', ascending=False);


fig = px.bar(dates_count,
             x='created_at', 
             y='contributions', title = 'contributions of the accounts posted/commented the same month they were created')
fig.update_traces(marker_color='#5296dd',
                  marker_line_width=0.5, opacity=1, textposition='auto').update_layout()
fig.show()


# THE SAME WEEK
# check for the date these accounts posted/commented
reddit_7 = df_merged[df_merged['days_after_creation'] <= 7]

dates_count_7 = df_merged.groupby(reddit_7['created_at'].dt.date).size().reset_index(name='contributions')
dates_count_7.sort_values('contributions', ascending=False);


fig = px.bar(dates_count_7,
             x='created_at', 
             y='contributions', title = 'contributions of the accounts posted/commented the same week they were created')
fig.update_traces(marker_color='#5296dd',
                  marker_line_width=0.5, opacity=1, textposition='auto').update_layout()
fig.show()


# THE SAME DAY
# check for the date these accounts posted/commented
reddit_1 = df_merged[df_merged['days_after_creation'] <= 0]

dates_count_1 = df_merged.groupby(reddit_1['created_at'].dt.date).size().reset_index(name='contributions')
dates_count_1.sort_values('contributions', ascending=False);


fig = px.bar(dates_count_1,
             x='created_at', 
             y='contributions', title = 'contributions of the accounts posted/commented the same day they were created')
fig.update_traces(marker_color='#5296dd',
                  marker_line_width=0.5, opacity=1, textposition='auto').update_layout()
fig.show()


# get the author names that commented in a negative way the same month the account was created
# to add to the suspected list
df_merged_30 = df_merged.query("days_after_creation <= 30 & sentiment_blob == sentiment_nltk == 'Negative' ")
df_merged_30.head()


# group by creation year and count 
df_contributions = df_merged.groupby(df_merged['user_created_at'].dt.year).size().reset_index(name='n_accounts')

fig = px.bar(df_contributions,
             x='user_created_at', y='n_accounts', text='n_accounts', title='Number of User Accounts Created in each year / having contributions in 2019')
fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


fig = px.bar(df.groupby(df['created_at'].dt.month).size().reset_index(name='contribution_count'),
             x='created_at', y='contribution_count', text='contribution_count')

fig.update_layout(
            title={
        'text': "Estimation of the number contributions created in each month of 2019",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_layout(
    xaxis = dict(
        title='Month(2019)',
        tickmode = 'array',
        tickvals = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
        ticktext = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
        )
)

clrs = ['red' if (y > 4000) else '#5296dd' for y in df.groupby(df['created_at'].dt.month).size()] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


fig = px.bar(df.groupby(df['created_at'].dt.day).size().reset_index(name='contribution_count'),
             x='created_at', y='contribution_count', text='contribution_count')

fig.update_layout(
            title={
        'text': "Estimation of the number contributions created in each DayOfMonth in 2019",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_layout(
    xaxis = dict(
        title='Month Days(2019)',
        tickmode = 'linear',
    )
)



clrs = ['red' if (y > 1500) else '#5296dd' for y in df.groupby(df['created_at'].dt.day).size()] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


week_day = df['created_at'].dt.strftime('%a')
# one can sort by any order by providing a custom index explicitely :
# https://stackoverflow.com/questions/43855474/changing-sort-in-value-counts/43855492
week_sorted = week_day.value_counts()[['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']]
week_sorted

Mon    2742
Tue    2693
Wed    3111
Thu    3980
Fri    5523
Sat    3291
Sun    2338
Name: created_at, dtype: int64


fig = px.bar(df.groupby(df['created_at'].dt.dayofweek).size().reset_index(name='contribution_count'),
             x='created_at', y='contribution_count', text='contribution_count')

fig.update_layout(
            title={
        'text': "Estimation of the number contributions created in each DayOfWeek (2019)",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_layout(
    xaxis = dict(
        title='DayOfWeek(2019)',
        tickmode = 'array',
        tickvals = [0, 1, 2, 3, 4, 5, 6],
        ticktext = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']
        )
)

clrs = ['red' if (y > 4000) else '#5296dd' for y in df.groupby(df['created_at'].dt.dayofweek).size()] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


# check for the hour the contributions were made
df_hours = df.groupby(df['created_at'].dt.hour).size().reset_index(name='contribution_count')
# df_hours.sort_values('contribution_count', ascending=False);   


fig = px.bar(df_hours,
             x='created_at', y='contribution_count', 
             title='Number of contrbutions Comment/Submission in day hours (2019)')

fig.update_layout(
    xaxis = dict(
        title='Hours of Day',
        tickmode = 'linear',
        dtick = 1
    )
)

fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


df.created_at.dt.date.value_counts().head()

2019-03-15    3221
2019-03-14    1844
2019-03-13    1170
2019-03-16     818
2019-03-02     505
Name: created_at, dtype: int64


trendy_dates = df.groupby(df['created_at'].dt.date).size().reset_index(name='contribution_count')

fig = px.bar(trendy_dates,
             x='created_at', y='contribution_count')

fig.update_layout(
            title={
        'text': "The number of contributions created in each date",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_traces(marker_color='#5296dd',
                  marker_line_width=0.5, opacity=1, textposition='auto').update_layout()
fig.show()


top_trendy_dates = trendy_dates.sort_values('contribution_count', ascending=False).head(5)


top_trendy_dates


fig = px.bar(top_trendy_dates,
             x='created_at', y='contribution_count', title='Number of contrbutions Comment/Submission in trendy dates')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = top_trendy_dates.created_at,
    )
)

clrs = ['red' if (y > 400) else '#5296dd' for y in top_trendy_dates.contribution_count] 

fig.update_traces(marker_color=clrs,
                  opacity=1, textposition='auto').update_layout()

# marker_line_width=1.5,

fig.show()


def peack_days(date):
    print(f'How many users contributed on the peak day ({date})')
    print(df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == date].user_name.nunique())
    print(df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == date].user_name.shape)
    print('Years')
    df_merged_peak1 = df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == date]
    


    # check for the year the accounts were created
    df_user_year1 = df_merged_peak1.groupby(df_merged_peak1['user_created_at'].dt.year).size().reset_index(name='contribution_count')

    fig = px.bar(df_user_year1,
                 x='user_created_at', y='contribution_count', 
                 title=f'The creation year of the accounts contributed on the peak day ({date})')

    fig.update_layout(
        xaxis = dict(
            title='Accout Creation Year',
            tickmode = 'linear',
            dtick = 1
        )
    )

    clrs = ['red' if (y > 250) else '#5296dd' for y in df_user_year1.contribution_count] 

    fig.update_traces(marker_color=clrs,
                      marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
    fig.show()
    
    print('hours')
    
    df_peak_1 = df[df.created_at.dt.strftime('%Y-%m-%d') == f'{date}']

    # check for the hour the contributions were made
    df_hours = df_peak_1.groupby(df['created_at'].dt.hour).size().reset_index(name='contribution_count')
    # df_hours.sort_values('contribution_count', ascending=False);   


    fig2 = px.bar(df_hours,
                 x='created_at', y='contribution_count', 
                 title='Number of contrbutions Comment/Submission in day hours')

    fig2.update_layout(
        xaxis = dict(
            title='Hours of Day',
            tickmode = 'linear',
            dtick = 1
        )
    )

    clrs = ['red' if (y > 80) else '#5296dd' for y in df_hours.contribution_count] 

    fig2.update_traces(marker_color=clrs,
                      marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
    fig2.show()


top_trendy_dates


peack_days('2019-03-15')

How many users contributed on the peak day (2019-03-15)
1553
(3221,)
Years

hours


peack_days('2019-03-14')

How many users contributed on the peak day (2019-03-14)
893
(1844,)
Years

hours


peack_days('2019-03-13')

How many users contributed on the peak day (2019-03-13)
536
(1170,)
Years

hours


peack_days('2019-03-16')

How many users contributed on the peak day (2019-03-16)
466
(818,)
Years

hours


peack_days('2019-03-02')

How many users contributed on the peak day (2019-03-02)
275
(505,)
Years

hours

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t3_atwt8e	/r/lukomorye/comments/atwt8e/amber_heard_z835/	Amber Heard (z835)	NaN	r/lukomorye	Sovetika	2019-02-23 15:56:02	Neutral	Neutral	1.0	NaN	submission	3	amber_heard_z835	3	[]
1	t3_awifd6	/r/lukomorye/comments/awifd6/amber_heard_z982/	Amber Heard (z982)	NaN	r/lukomorye	Sovetika	2019-03-02 14:47:24	Neutral	Neutral	1.0	NaN	submission	3	amber_heard_z982	3	[]
2	t3_awn4ia	/r/lukomorye/comments/awn4ia/amber_heard_z1001/	Amber Heard (z1001)	NaN	r/lukomorye	Sovetika	2019-03-02 22:18:46	Neutral	Neutral	1.0	NaN	submission	3	amber_heard_z1001	3	[]
3	t3_awtsku	/r/lukomorye/comments/awtsku/amber_heard_z1008/	Amber Heard (z1008)	NaN	r/lukomorye	Sovetika	2019-03-03 13:01:10	Neutral	Neutral	1.0	NaN	submission	3	amber_heard_z1008	3	[]
4	t3_awz0k4	/r/lukomorye/comments/awz0k4/amber_heard_z1011/	Amber Heard (z1011)	NaN	r/lukomorye	Sovetika	2019-03-03 21:46:41	Neutral	Neutral	1.0	NaN	submission	3	amber_heard_z1011	3	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
20	t3_abeu1p	/r/JerkOffToCelebs/comments/abeu1p/i_cant_stop_cumming_to_amber_heard_after_seeing/	I can't stop cumming to Amber Heard after seeing her in Aquaman	NaN	r/JerkOffToCelebs	jackstave	2019-01-01 04:15:42	Neutral	Positive	130.0	NaN	submission	12	i_cant_stop_cumming_to_amber_heard_after_seeing	9	[]
38	t3_abfc1j	/r/goddesses/comments/abfc1j/amber_heard/	Amber Heard	NaN	r/goddesses	latimeriachalumnae	2019-01-01 05:20:39	Neutral	Neutral	222.0	NaN	submission	2	amber_heard	2	[]
39	t3_abfcjd	/r/Celebs/comments/abfcjd/amber_heard/	Amber Heard	NaN	r/Celebs	latimeriachalumnae	2019-01-01 05:22:16	Neutral	Neutral	268.0	NaN	submission	2	amber_heard	2	[]
46	t3_abfjpu	/r/Amber_Heard/comments/abfjpu/all_amber_heard_scenes_on_never_back_down/	All Amber Heard Scenes On Never Back Down	NaN	r/Amber_Heard	Devilnomi	2019-01-01 05:48:38	Negative	Neutral	1.0	NaN	submission	8	Amber_Heard	2	[]
59	t3_abgjob	/r/JerkOffToCelebs/comments/abgjob/just_watched_aquaman_and_it_got_me_thinking_about/	Just watched Aquaman and it got me thinking about Amber Heard	NaN	r/JerkOffToCelebs	NOTXnxxstaff	2019-01-01 08:21:12	Neutral	Neutral	546.0	NaN	submission	11	just_watched_aquaman_and_it_got_me_thinking_about	9	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
362	t3_adjb6m	/r/celebJObuds/comments/adjb6m/anyone_down_for_an_amber_heard_joi_or_rp/	Anyone down for an Amber Heard Joi or RP?	NaN	r/celebJObuds	-banned-	2019-01-07 16:29:01	Negative	Neutral	1.0	NaN	submission	9	anyone_down_for_an_amber_heard_joi_or_rp	9	[]
728	t1_ee9aycj	/r/JerkOffToCelebs/comments/agm8rd/amber_heard_from_the_rear_where_would_you_cum_on/ee9aycj/	Gonna have to bury my cock in Amber Heards ass and unload my balls in it. The tightness of Amber's butthole would feel so good on my throbbing cock	t3_agm8rd	r/JerkOffToCelebs	MelissaBenoistQueen	2019-01-17 07:11:35	Positive	Neutral	2.0	submission	comment	29	amber_heard_from_the_rear_where_would_you_cum_on	10	[]
995	t3_ak1jmn	/r/CelebAssPussyMouth/comments/ak1jmn/apm_amber_heard_kate_upton_and_sophie_turner/	APM Amber Heard, Kate Upton and Sophie Turner, which bombshell gets what?	NaN	r/CelebAssPussyMouth	-banned-	2019-01-26 15:02:49	Neutral	Neutral	1.0	NaN	submission	12	apm_amber_heard_kate_upton_and_sophie_turner	8	[]
1491	t3_am40fb	/r/sweepstakes/comments/am40fb/muvas_vday_giveaway_win_a_massive_personal_care/	MUVA's Vday giveaway - win a massive personal care, beauty, and sex prize package from Amber Heard and Slut Box! {US} (02/06/19)	NaN	r/sweepstakes	-banned-	2019-02-01 16:49:21	Positive	Neutral	2.0	NaN	submission	22	muvas_vday_giveaway_win_a_massive_personal_care	8	[]
1492	t3_am40fp	/r/giveaways/comments/am40fp/muvas_vday_giveaway_win_a_massive_personal_care/	MUVA's Vday giveaway - win a massive personal care, beauty, and sex prize package from Amber Heard and Slut Box! {US} (02/06/19)	NaN	r/giveaways	-banned-	2019-02-01 16:49:23	Positive	Neutral	1.0	NaN	submission	22	muvas_vday_giveaway_win_a_massive_personal_care	8	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls	urls_count
2620	t1_ehkshd6	/r/movies/comments/aw8x9o/johnny_depp_sues_amb...	For those who dont wanna click and are out of ...	t3_aw8x9o	r/movies	friedchickenpaws	2019-03-01 19:59:53	Positive	Negative	32.0	submission	comment	46	johnny_depp_sues_amber_heard_for_50_million	8	[]	0
2632	t3_aw9hyc	/r/newsfeedmedia/comments/aw9hyc/johnny_depp_s...	Johnny Depp sues ex-wife Amber Heard for $50mi...	NaN	r/newsfeedmedia	newsfeedmedia	2019-03-01 20:44:43	Neutral	Negative	1.0	NaN	submission	11	johnny_depp_sues_exwife_amber_heard_for_50million	8	[]	0
2647	t3_awaf1d	/r/MensRights/comments/awaf1d/johnny_depp_sues...	Johnny Depp sues ex-wife Amber Heard for $50mi...	NaN	r/MensRights	JohannReddit	2019-03-01 22:11:40	Neutral	Negative	327.0	NaN	submission	11	johnny_depp_sues_exwife_amber_heard_for_50million	8	[]	0
2759	t1_ehm5r6g	/r/entertainment/comments/awcjfw/johnny_depp_f...	Using finances to threaten, intimidate, or hur...	t3_awcjfw	r/entertainment	I_Heart_Squids	2019-03-02 08:05:10	Positive	Negative	-9.0	submission	comment	195	johnny_depp_files_50_million_defamation_lawsuit	7	['https://www.washingtonpost.com', 'https://pe...	2
2792	t3_awgee8	/r/INDEPENDENTauto/comments/awgee8/arts_johnny...	[Arts] - Johnny Depp sues ex-wife Amber Heard ...	NaN	r/INDEPENDENTauto	AutoNewsAdmin	2019-03-02 10:15:41	Neutral	Negative	1.0	NaN	submission	15	arts_johnny_depp_sues_exwife_amber_heard_for_50m	9	[]	0

	index	author
0	-banned-	4487
1	AutoModerator	426
2	CelebBattleVoteBot	120
3	spells010	80
4	Dannig178	70
5	5th_Law_of_Robotics	68
6	newsfeedmedia	62
7	SakuOtaku	57
8	Sovetika	48
9	bufedad	43

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls	urls_count
0	t1_ek959vk	/r/CelebBattles/comments/ba5rm3/amber_heard_vs...	Vote here: https://www.strawpoll.me/17754197\n...	t3_ba5rm3	r/CelebBattles	CelebBattleVoteBot	2019-04-06 16:01:40	Positive	Neutral	1.0	submission	comment	14	amber_heard_vs_scarlett_johansson	5	['https://www.strawpoll.me', 'https://www.stra...	2
1	t1_ekb5hq0	/r/CelebBattles/comments/bafs1y/emmy_rossum_vs...	Vote here: https://www.strawpoll.me/17759820\n...	t3_bafs1y	r/CelebBattles	CelebBattleVoteBot	2019-04-07 12:33:12	Positive	Neutral	1.0	submission	comment	14	emmy_rossum_vs_amber_heard	5	['https://www.strawpoll.me', 'https://www.stra...	2
2	t1_ekn9rsu	/r/CelebBattles/comments/ba5rm3/amber_heard_vs...	Winner of this battle: Scarlett Johansson\n\nT...	t3_ba5rm3	r/CelebBattles	CelebBattleVoteBot	2019-04-11 17:29:07	Positive	Neutral	1.0	submission	comment	49	amber_heard_vs_scarlett_johansson	5	['https://i.imgur.com']	1
3	t1_ekq1i7x	/r/CelebBattles/comments/bafs1y/emmy_rossum_vs...	Winner of this battle: Amber Heard\n\nTotal vo...	t3_bafs1y	r/CelebBattles	CelebBattleVoteBot	2019-04-12 15:31:43	Positive	Neutral	1.0	submission	comment	49	emmy_rossum_vs_amber_heard	5	['https://i.imgur.com']	1
4	t1_ektma74	/r/CelebBattles/comments/bcuxqa/amber_heard_vs...	Vote here: https://www.strawpoll.me/17810144\n...	t3_bcuxqa	r/CelebBattles	CelebBattleVoteBot	2019-04-13 20:35:22	Positive	Neutral	1.0	submission	comment	14	amber_heard_vs_melissa_benoist	5	['https://www.strawpoll.me', 'https://www.stra...	2

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t3_ckz6p7	/r/u_spells010/comments/ckz6p7/how_can_i_meet_...	how can i meet Amber Heard ( +91 9116496706 cl...	NaN	u/spells010	spells010	2019-08-02 04:15:17	Neutral	Positive	1.0	NaN	submission	15	u_spells010	2	[]
1	t3_ckz9bk	/r/u_spells010/comments/ckz9bk/powerful_attrac...	powerful attraction love spell for Amber Heard...	NaN	u/spells010	spells010	2019-08-02 04:22:56	Positive	Positive	1.0	NaN	submission	16	u_spells010	2	[]
2	t3_ckzdq9	/r/u_spells010/comments/ckzdq9/how_to_become_b...	how to become boyfriend Amber Heard ( +91 9116...	NaN	u/spells010	spells010	2019-08-02 04:35:57	Neutral	Positive	1.0	NaN	submission	15	u_spells010	2	[]
3	t3_ckzgcm	/r/u_spells010/comments/ckzgcm/how_to_become_g...	how to become girlfriend Amber Heard ( +91 911...	NaN	u/spells010	spells010	2019-08-02 04:43:50	Neutral	Positive	1.0	NaN	submission	15	u_spells010	2	[]
4	t3_ckzh9t	/r/u_spells010/comments/ckzh9t/how_to_connect_...	how to connect love relationship with Amber He...	NaN	u/spells010	spells010	2019-08-02 04:46:32	Positive	Positive	1.0	NaN	submission	17	u_spells010	2	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t3_ais5uh	/r/celeb_blondes/comments/ais5uh/amber_heard/	Amber Heard	NaN	r/celeb_blondes	Dannig178	2019-01-22 22:01:53	Neutral	Neutral	68.0	NaN	submission	2	celeb_blondes	2	[]
1	t3_ajcvsb	/r/CelebrityButts/comments/ajcvsb/amber_heard/	Amber Heard	NaN	r/CelebrityButts	Dannig178	2019-01-24 14:22:39	Neutral	Neutral	59.0	NaN	submission	2	amber_heard	2	[]
2	t1_ef6dc8n	/r/TrueFMK/comments/ako0za/amber_heard_gal_gad...	FMK	t3_ako0za	r/TrueFMK	Dannig178	2019-01-28 14:56:31	Neutral	Neutral	15.0	submission	comment	1	amber_heard_gal_gadot_margot_robbie	6	[]
3	t3_algbcp	/r/CelebrityPokies/comments/algbcp/amber_heard/	Amber Heard	NaN	r/CelebrityPokies	Dannig178	2019-01-30 19:21:00	Neutral	Neutral	32.0	NaN	submission	2	amber_heard	2	[]
4	t3_amf3f6	/r/BralessCelebs/comments/amf3f6/amber_heard/	Amber Heard	NaN	r/BralessCelebs	Dannig178	2019-02-02 15:35:11	Neutral	Neutral	20.0	NaN	submission	2	amber_heard	2	[]

	created_at	n_contributions
44	2019-10-31	4
23	2019-05-07	3
30	2019-06-15	2
21	2019-04-13	2
28	2019-06-10	2
27	2019-06-08	2
35	2019-07-23	2
36	2019-07-25	2
24	2019-05-18	2
10	2019-03-01	2

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t1_ehzsb1t	/r/WeinsteinEffect/comments/axbq7t/johnny_depp...	Lets hope he gets justice if what he's saying ...	t3_axbq7t	r/WeinsteinEffect	5th_Law_of_Robotics	2019-03-07 14:05:02	Positive	Positive	3.0	submission	comment	11	johnny_depp_sues_exwife_amber_heard_over_me_too	9	[]
1	t1_eif82ty	/r/WeinsteinEffect/comments/b0h5wa/why_some_pe...	>"Unaware that members of Mr. Depp's security ...	t3_b0h5wa	r/WeinsteinEffect	5th_Law_of_Robotics	2019-03-13 11:34:38	Negative	Neutral	41.0	submission	comment	126	why_some_people_are_uncanceling_johnny_depp_in	8	[]
2	t1_eif842s	/r/WeinsteinEffect/comments/b0h5wa/why_some_pe...	> Idk at the time, it really did seem like h...	t1_eieox9f	r/WeinsteinEffect	5th_Law_of_Robotics	2019-03-13 11:35:19	Negative	Neutral	-6.0	comment	comment	57	why_some_people_are_uncanceling_johnny_depp_in	8	[]
3	t1_eif8cvt	/r/WeinsteinEffect/comments/b0h5wa/why_some_pe...	>So apparently the Amber Heard case wasn't as ...	t1_eiemnna	r/WeinsteinEffect	5th_Law_of_Robotics	2019-03-13 11:40:17	Positive	Negative	6.0	comment	comment	91	why_some_people_are_uncanceling_johnny_depp_in	8	[]
4	t1_eif8eqs	/r/WeinsteinEffect/comments/b0h5wa/why_some_pe...	In a just world this would end her career.\n\n...	t1_eif6z6o	r/WeinsteinEffect	5th_Law_of_Robotics	2019-03-13 11:41:21	Negative	Negative	17.0	comment	comment	27	why_some_people_are_uncanceling_johnny_depp_in	8	[]

	created_at	n_contributions
1	2019-03-13	36
2	2019-03-14	11
4	2019-03-24	7
9	2019-09-11	5
5	2019-03-26	3
0	2019-03-07	1
3	2019-03-23	1
6	2019-07-27	1
7	2019-07-30	1
8	2019-08-30	1
10	2019-09-12	1

	created_at	n_contributions
15	2019-04-12	2
26	2019-05-13	2
51	2019-10-11	2
17	2019-04-14	2
30	2019-05-17	2
42	2019-08-16	1
32	2019-05-25	1
33	2019-05-26	1
34	2019-06-13	1
35	2019-07-02	1

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t1_ehpfh5i	/r/GamerGhazi/comments/awsjlq/johnny_depp_sues...	Didn't he even agree that she wasn't lying dur...	t3_awsjlq	r/GamerGhazi	SakuOtaku	2019-03-03 16:33:27	Positive	Neutral	21.0	submission	comment	29	johnny_depp_sues_amber_heard_over_metoo_article	8	[]
1	t1_ehpgzu6	/r/GamerGhazi/comments/awsjlq/johnny_depp_sues...	He's had history of being violent on set, and ...	t1_ehpg2x3	r/GamerGhazi	SakuOtaku	2019-03-03 16:53:26	Negative	Negative	25.0	comment	comment	31	johnny_depp_sues_amber_heard_over_metoo_article	8	[]
2	t3_axbq7t	/r/WeinsteinEffect/comments/axbq7t/johnny_depp...	Johnny Depp sues ex-wife Amber Heard Over Me T...	NaN	r/WeinsteinEffect	SakuOtaku	2019-03-04 20:12:30	Neutral	Neutral	24.0	NaN	submission	10	johnny_depp_sues_exwife_amber_heard_over_me_too	9	[]
3	t1_ehsgdug	/r/WeinsteinEffect/comments/axbq7t/johnny_depp...	I thought it was worth posting here, though fr...	t3_axbq7t	r/WeinsteinEffect	SakuOtaku	2019-03-04 20:15:16	Positive	Neutral	8.0	submission	comment	31	johnny_depp_sues_exwife_amber_heard_over_me_too	9	[]
4	t3_b0h5wa	/r/WeinsteinEffect/comments/b0h5wa/why_some_pe...	Why Some People Are 'Uncanceling' Johnny Depp ...	NaN	r/WeinsteinEffect	SakuOtaku	2019-03-13 03:24:23	Neutral	Negative	257.0	NaN	submission	15	why_some_people_are_uncanceling_johnny_depp_in	8	[]

	created_at	n_contributions
2	2019-03-13	19
3	2019-03-14	15
8	2019-05-22	11
4	2019-03-16	4
0	2019-03-03	2
1	2019-03-04	2
5	2019-04-12	2
6	2019-04-13	1
7	2019-04-14	1

	created_at	n_contributions
22	2019-11-01	4
6	2019-03-24	3
9	2019-05-14	2
0	2019-01-04	1
17	2019-08-21	1
29	2019-12-21	1
28	2019-12-17	1
27	2019-12-01	1
26	2019-11-26	1
25	2019-11-19	1
24	2019-11-09	1
23	2019-11-04	1
21	2019-10-14	1
20	2019-10-10	1
19	2019-10-09	1
18	2019-10-07	1
15	2019-08-19	1
16	2019-08-20	1
1	2019-01-22	1
14	2019-08-09	1
13	2019-08-08	1
12	2019-08-07	1
11	2019-06-03	1
10	2019-05-30	1
8	2019-05-12	1
7	2019-05-10	1
5	2019-03-13	1
4	2019-03-04	1
3	2019-02-16	1
2	2019-01-28	1
30	2019-12-28	1

	created_at	n_contributions
6	2019-06-27	23
5	2019-05-04	17
1	2019-03-02	2
2	2019-03-03	2
4	2019-03-15	2
0	2019-02-23	1
3	2019-03-04	1

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
3937	GRJR721	True	True	False	False	891.0	167792.0	2011-11-15 20:48:23	others	others
4432	AutoModerator	True	True	True	False	1000.0	1000.0	2012-01-05 05:24:28	others	others

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
26	t1_eczrb8l	/r/JerkOffToCelebs/comments/abeu1p/i_cant_stop...	Fucking same dude, her tits were the best part...	t3_abeu1p	r/JerkOffToCelebs	-banned-	2019-01-01 04:23:22	Positive	Neutral	20.0	submission	comment	12	i_cant_stop_cumming_to_amber_heard_after_seeing	9	[]
33	t1_eczsup6	/r/DC_Cinematic/comments/abc2ip/other_amber_he...	Suuure, keep believing her bullshit. A picture...	t1_eczrlhn	r/DC_Cinematic	Tedinasuit	2019-01-01 04:51:41	Negative	Negative	4.0	comment	comment	69	DC_Cinematic	2	[]
48	t1_eczwpte	/r/JerkOffToCelebs/comments/abeu1p/i_cant_stop...	I’m in the same boat as you, she looked fuckin...	t3_abeu1p	r/JerkOffToCelebs	-banned-	2019-01-01 06:04:50	Positive	Positive	5.0	submission	comment	11	i_cant_stop_cumming_to_amber_heard_after_seeing	9	[]
55	t1_ed00x21	/r/DC_Cinematic/comments/abc2ip/other_amber_he...	She’s been arrested for domestic violence agai...	t1_eczv03v	r/DC_Cinematic	mich_m	2019-01-01 07:37:27	Negative	Neutral	15.0	comment	comment	28	DC_Cinematic	2	[]
140	t1_ed3ljqt	/r/pickoneceleb/comments/ab8072/gal_gadot_ambe...	Margot. \n\nIn order from left to right I woul...	t3_ab8072	r/pickoneceleb	juanathanluis	2019-01-02 20:21:41	Positive	Neutral	3.0	submission	comment	12	gal_gadot_amber_heard_or_margot_robbie_describe	8	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
261	t3_aco2tz	/r/JerkOffToCelebs/comments/aco2tz/id_give_a_lot_to_fuck_amber_heard_doggy_style_on/	I’d give a lot to fuck Amber Heard doggy style on that beach	NaN	r/JerkOffToCelebs	Count_Fapula1	2019-01-04 23:26:38	Negative	Negative	46.0	NaN	submission	13	id_give_a_lot_to_fuck_amber_heard_doggy_style_on	11	[]
825	t3_airyf8	/r/JerkOffToCelebs/comments/airyf8/amber_heard_is_fucking_hot/	Amber Heard is fucking hot	NaN	r/JerkOffToCelebs	-banned-	2019-01-22 21:43:12	Positive	Neutral	1.0	NaN	submission	5	amber_heard_is_fucking_hot	5	[]
1124	t3_aksanw	/r/JerkOffToCelebs/comments/aksanw/dc_ladies_battle_would_you_rather_fuck_gal_gadot/	DC Ladies battle. Would you rather fuck Gal Gadot, Margot Robbie, Amber Heard Or Amy Adams?	NaN	r/JerkOffToCelebs	-banned-	2019-01-28 21:26:59	Negative	Negative	55.0	NaN	submission	16	dc_ladies_battle_would_you_rather_fuck_gal_gadot	9	[]
2262	t3_ar5k1d	/r/JerkOffToCelebs/comments/ar5k1d/amber_heard_is_so_fuckable/	Amber Heard is so fuckable	NaN	r/JerkOffToCelebs	-banned-	2019-02-16 05:04:05	Neutral	Neutral	182.0	NaN	submission	5	amber_heard_is_so_fuckable	5	[]
3643	t3_ax1ds1	/r/teenagers/comments/ax1ds1/seriously_fuck_amber_heard/	Seriously Fuck Amber Heard	NaN	r/teenagers	-banned-	2019-03-04 01:44:30	Negative	Negative	6.0	NaN	submission	4	seriously_fuck_amber_heard	4	[]

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
13888	Dannig178	True	True	True	False	2765.0	982410.0	2014-05-14 14:35:40	others	others
50713	spells010	True	False	False	False	0.0	1.0	2019-07-31 04:00:33	others	2019

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
483	t1_edjnjw0	/r/TrueFMK/comments/adrm64/dcmarvel_superbabes_gal_gadot_brie_larson_amber/edjnjw0/	Thanks for your post /u/Pillowcasetalk123. Remember to RATE YOUR OWN POST, and do not delete it within 30 days. First offense gets a warning, repeat offenses may result in a ban. Please limit new submissions to five per day.\n\nI am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/TrueFMK) if you have any questions or concerns.	t3_adrm64	r/TrueFMK	AutoModerator	2019-01-08 06:48:02	Positive	Neutral	1.0	submission	comment	63	dcmarvel_superbabes_gal_gadot_brie_larson_amber	7	[]
487	t1_edjo84a	/r/TrueFMK/comments/adrm64/dcmarvel_superbabes_gal_gadot_brie_larson_amber/edjo84a/	Here are the FMK tallies so far (bot v2): \n \n\|\|1\|2\|3\n:-:\|:-:\|:-:\|:-:\nF\|26% (9)\|32% (11)\|41% (14)\|\n M\|47% (16)\|20% (7)\|32% (11)\|\n K\|26% (9)\|47% (16)\|26% (9)\|\n \n\nTotal Votes: 34 \\| Last Updated: 2019-01-15T14:47:03+0000\n\nVote by including the three letters at the start of a top level comment. This tally updates every 15 minutes, and stops updating when the submission is 7 days old.	t3_adrm64	r/TrueFMK	FMKBot	2019-01-08 07:01:10	Positive	Positive	2.0	submission	comment	60	dcmarvel_superbabes_gal_gadot_brie_larson_amber	7	[]
488	t1_edjo90l	/r/TrueFMK/comments/adrm64/dcmarvel_superbabes_gal_gadot_brie_larson_amber/edjo90l/	KFM on this pic and the eyes/hair. Ambers boobs made an appearance in my calculations as well. I am only sure about M though. That unrealistic red hair with blue eyes combo is my weakness. Just like the recent WWE post.	t3_adrm64	r/TrueFMK	PM_ME_UR_PIG-TAILS	2019-01-08 07:01:40	Neutral	Neutral	3.0	submission	comment	41	dcmarvel_superbabes_gal_gadot_brie_larson_amber	7	[]
502	t1_edjxpsc	/r/TrueFMK/comments/adrm64/dcmarvel_superbabes_gal_gadot_brie_larson_amber/edjxpsc/	Fmk	t3_adrm64	r/TrueFMK	throwedrollss	2019-01-08 11:05:02	Neutral	Neutral	1.0	submission	comment	1	dcmarvel_superbabes_gal_gadot_brie_larson_amber	7	[]
515	t1_edk65sc	/r/TrueFMK/comments/adrm64/dcmarvel_superbabes_gal_gadot_brie_larson_amber/edk65sc/	FMK\n\nF - thanks to Natalie Portman before her, I have a thing for /r/JewishGoddesses, toned, tall brunette\n\nM - I am growing to like her. I like the smirk. Great body. Like her open/round eyes.\n\nK - crazy, the unrealistic hair color mehs her for me, boobs aren't much different from Brie's	t3_adrm64	r/TrueFMK	naedthrowaway	2019-01-08 13:59:40	Negative	Positive	3.0	submission	comment	53	dcmarvel_superbabes_gal_gadot_brie_larson_amber	7	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
357	t1_edh8kss	/r/celebnsfw/comments/adhbsj/amber_heard/edh8kss/	what did she hear?	t3_adhbsj	r/celebnsfw	cuacuacuac	2019-01-07 15:39:49	Neutral	Neutral	3.0	submission	comment	4	amber_heard	2	[]
534	t1_edl7vr6	/r/goddesses/comments/adxeru/amber_heard/edl7vr6/	But what did she hear?	t3_adxeru	r/goddesses	-TheExtraMile-	2019-01-08 21:44:48	Neutral	Neutral	3.0	submission	comment	5	amber_heard	2	[]
12685	t1_ejvogca	/r/geekboners/comments/b83lax/aquaman_amber_he...	what did she hear?	t3_b83lax	r/geekboners	mattreyu	2019-04-01 15:39:54	Neutral	Neutral	0.0	submission	comment	4	aquaman_amber_heard	3	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
5479	t3_b0x9co	/r/WeinsteinEffect/comments/b0x9co/johnny_depp_was_abused_by_exwife_amber_heard_new/	Johnny Depp was abused by ex-wife Amber Heard, new evidence shows \| Entertainment - Geo.tv	NaN	r/WeinsteinEffect	Lingenfelter	2019-03-14 07:09:49	Positive	Neutral	411.0	NaN	submission	15	johnny_depp_was_abused_by_exwife_amber_heard_new	9	[]
5539	t3_b10l31	/r/news/comments/b10l31/johnny_depp_was_abused_by_exwife_amber_heard_new/	Johnny Depp was abused by ex-wife Amber Heard, new evidence shows	NaN	r/news	-banned-	2019-03-14 13:51:49	Positive	Negative	1.0	NaN	submission	11	johnny_depp_was_abused_by_exwife_amber_heard_new	9	[]
5540	t3_b10ld3	/r/worldnews/comments/b10ld3/johnny_depp_was_abused_by_exwife_amber_heard_new/	Johnny Depp was abused by ex-wife Amber Heard, new evidence shows	NaN	r/worldnews	Soupjoe5	2019-03-14 13:52:36	Positive	Negative	4552.0	NaN	submission	11	johnny_depp_was_abused_by_exwife_amber_heard_new	9	[]
5542	t3_b10p3q	/r/news/comments/b10p3q/johnny_depp_was_abused_by_exwife_amber_heard_new/	Johnny Depp was abused by ex-wife Amber Heard, new evidence shows	NaN	r/news	-banned-	2019-03-14 14:02:20	Positive	Negative	1.0	NaN	submission	11	johnny_depp_was_abused_by_exwife_amber_heard_new	9	[]
5547	t3_b10qx2	/r/news/comments/b10qx2/johnny_depp_was_abused_by_exwife_amber_heard_new/	Johnny Depp was abused by ex-wife Amber Heard, new evidence shows	NaN	r/news	-banned-	2019-03-14 14:06:58	Positive	Negative	1.0	NaN	submission	11	johnny_depp_was_abused_by_exwife_amber_heard_new	9	[]

	author	n_contributions
3	-banned-	778
1674	guac_boi1	36
893	Pixelated_Piracy	34
1877	majortom106	29
514	HawkofDarkness	25
1061	Slyndrr	21
561	Ignorant_Slut	19
176	BrobaFett115	19
378	EarlyEndTimes	16
2092	sajeebooty	16

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
13687	Pixelated_Piracy	True	False	False	False	25092.0	257.0	2014-04-25 07:16:31	others	others
27101	guac_boi1	True	False	False	False	56749.0	6786.0	2017-01-09 23:31:59	others	others
27341	majortom106	True	False	False	False	26689.0	8313.0	2017-01-22 22:02:53	others	others

Case Study: Reddit Social Network Analysis Against Influence Operation¶

Table of Contents¶

Introduction¶

Exploratory Data Analysis¶

Reddit Contributions (Comments / Submissions)¶

The # of submissions VS the # of comments¶

Most contributed user¶

Further Investigate The Most Commented Users In 2019¶

AutoModerator¶

CelebBattleVoteBot¶

spells010¶

Dannig178¶

5th_Law_of_Robotics¶

newsfeedmedia¶

SakuOtaku¶

Sovetika¶

Check wether the users with the most contributions are mod, gold or having a verified email¶

Investigate the text column¶

Investigate The Most Negative key Words Used (from the wordcloud map)¶

Lets first check for the users using the word 'f*ck'¶

juanathanluis¶

Check for the repeated text¶

Amber Heard¶

Amber Heard¶

Amber Heard¶

[Aquaman] Amber Heard¶

Johnny Depp was abused by ex-wife Amber Heard, new evidence shows¶

What did she hear?¶

Check the number of text words

Reddit Comments¶

The number of parent comments on submissions¶

Reddit Submission Data¶

Investigating the Submission Text (Submissions with the most comments and replies)

johnny_depp_was_abused_by_exwife_amber_heard_new¶

amber_heard¶

johnny_depp_files_50_million_defamation_lawsuit¶

johnny_depp_files_50_million_defamation_lawsuit¶

the_naked_truth_about_johnny_depp_case_and_what¶

petition_to_remove_accused_dv_perpetrator_amber¶

Invesigating the sumbissions with most comments (Top Level Comments)

Check the top 5 submissions in 2019¶

Define a function to create the mask and check if a submission text is part of the top 5 submissions¶

Check the authors of parent comments¶

Invesigating authors with the most submissions¶

Let us first Investigate authors with the most submissions¶

Check wether the users with the most submissions are mod, gold or having a verified email¶

Submission URLS¶

Check the number of submission text words

Subredits¶

Most used Subreddits¶

Merged Users Data with Comments & Submissions Data¶

Difference in time between creating the account and posting¶

Posting Duration After Account Creation¶

THE SAME MONTH:¶

THE SAME WEEK¶

THE SAME DAY¶

Estimation of Number of User Accounts Created in each year / having contributions in 2019¶

Peaks¶

Contributions count over Months in 2019¶

Contributions count over Days of month in 2019¶

In Which DayOfWeek users created more?¶

check for the hour the contributions were made (2019)¶

Which dates has the highest contrbitions for users?¶

How many users contributed on the peak day (March 15,2019)¶

How many users contributed on the peak day (March 14,2019)¶

How many users contributed on the peak day (March 13,2019)¶

How many users contributed on the peak day (March 16,2019)¶

How many users contributed on the peak day (March 2,2019)¶

Conclusions¶

Investigating the Submission Text
(Submissions with the most comments and replies)

Invesigating the sumbissions with most comments
(Top Level Comments)

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
29	RyanSmith	True	True	False	False	263666.0	5989322.0	2006-08-07 14:18:44	others	others
38	ukexpat	True	False	False	False	116030.0	37812.0	2006-09-26 14:31:15	others	others
52	davidreiss666	True	True	False	False	255369.0	2666725.0	2006-11-04 19:51:54	others	others
230	soundsoul	True	True	False	False	4156.0	238286.0	2008-01-04 02:52:49	others	others
237	MrGravityPants	True	False	False	False	21589.0	24628.0	2008-01-10 18:08:45	others	others
...	...	...	...	...	...	...	...	...	...	...
68709	GregDahl	True	True	True	True	NaN	NaN	NaT	banned	banned
68889	funlover24	True	True	True	True	NaN	NaN	NaT	banned	banned
68977	jarek212	True	True	True	True	NaN	NaN	NaT	banned	banned
70057	dhruvangrup	True	True	True	True	NaN	NaN	NaT	banned	banned
70281	HellsJuggernaut	True	True	True	True	NaN	NaN	NaT	banned	banned

	author	n_contributions
4	-banned-	1066
84	AutoModerator	116
202	Dannig178	47
705	RuleIV	39
218	DerHander	30
683	Rednaxela117	28
394	InfiniTitans	26
1263	imsrikant	20
1159	emilyguy	20
661	Queen1110	19

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
2664	t3_awcjfw	/r/entertainment/comments/awcjfw/johnny_depp_files_50_million_defamation_lawsuit/	Johnny Depp Files $50 Million Defamation Lawsuit Against Amber Heard	NaN	r/entertainment	RoyisOurBoy	2019-03-02 01:57:17	Neutral	Negative	2621.0	NaN	submission	10	johnny_depp_files_50_million_defamation_lawsuit	7	[]
2666	t3_awcm08	/r/movies/comments/awcm08/johnny_depp_files_50_million_defamation_lawsuit/	Johnny Depp files $50 million defamation lawsuit against Amber Heard	NaN	r/movies	-banned-	2019-03-02 02:05:26	Neutral	Negative	1.0	NaN	submission	10	johnny_depp_files_50_million_defamation_lawsuit	7	[]
2720	t3_aweu9e	/r/MensRights/comments/aweu9e/johnny_depp_files_50_million_defamation_lawsuit/	Johnny Depp Files $50 Million Defamation Lawsuit Against Ex-Wife Amber Heard After Her Op-Ed As A Purported Domestic Violence Victim.	NaN	r/MensRights	-banned-	2019-03-02 06:29:38	Negative	Negative	31.0	NaN	submission	20	johnny_depp_files_50_million_defamation_lawsuit	7	[]
2842	t3_awhqws	/r/worldnews/comments/awhqws/johnny_depp_files_50_million_defamation_lawsuit/	Johnny Depp files $50 million defamation lawsuit against Amber Heard	NaN	r/worldnews	aviralupdate	2019-03-02 13:26:22	Neutral	Negative	1.0	NaN	submission	10	johnny_depp_files_50_million_defamation_lawsuit	7	[]
2921	t3_awifxl	/r/news/comments/awifxl/johnny_depp_files_50_million_defamation_lawsuit/	Johnny Depp Files $50 Million Defamation Lawsuit Against Amber Heard, Calls Her Abuse Claims an ‘Elaborate Hoax’	NaN	r/news	rlw0312	2019-03-02 14:49:13	Positive	Negative	1.0	NaN	submission	17	johnny_depp_files_50_million_defamation_lawsuit	7	[]

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
12193	rlw0312	True	False	False	False	88393.0	15171.0	2013-12-14 04:32:50	others	others
17521	amigokomashiangeljr	True	True	False	False	9401.0	13615.0	2015-03-14 13:09:57	others	others
18709	RoyisOurBoy	False	False	False	False	26958.0	214143.0	2015-06-26 12:29:15	unverified	others
35070	hleb13	True	False	False	False	10267.0	20464.0	2018-02-23 21:38:07	others	2018
66028	aviralupdate	True	True	True	True	NaN	NaN	NaT	banned	banned
68681	przemkas	True	True	True	True	NaN	NaN	NaT	banned	banned

	author	n_contributions
2	-banned-	83
176	armoured_bobandi	21
251	masksnjunk	19
35	Doctah__Wahwee	12
116	PromiscuousMNcpl	9
245	littleliongirless	9
156	VanvanZandt	7
54	ForensicatingEdibles	7
185	bitter_truth_	7
291	sammythemc	7

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
11644	masksnjunk	True	False	False	False	21553.0	12571.0	2013-10-27 17:21:08	others	others
21402	Doctah__Wahwee	True	False	False	False	88115.0	663.0	2016-01-31 19:20:36	others	others
23142	armoured_bobandi	True	False	False	False	74298.0	844.0	2016-06-01 23:45:20	others	others

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls	urls_count
16235	t3_c4pw5a	/r/television/comments/c4pw5a/report_james_marsden_amber_heard_in_negotiations/	Report: James Marsden, Amber Heard in Negotiations to Star in The Stand Miniseries	NaN	r/television	sweetestdeth	2019-06-24 15:32:15	Neutral	Neutral	1674.0	NaN	submission	13	report_james_marsden_amber_heard_in_negotiations	7	[]	0
16370	t3_c4u6dy	/r/stephenking/comments/c4u6dy/report_james_marsden_amber_heard_in_negotiations/	Report: James Marsden, Amber Heard in Negotiations to Star in The Stand Miniseries	NaN	r/stephenking	tacocat-_-tacocat	2019-06-24 19:36:29	Neutral	Neutral	53.0	NaN	submission	13	report_james_marsden_amber_heard_in_negotiations	7	[]	0

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
24581	sweetestdeth	True	False	False	False	33784.0	39792.0	2016-08-21 19:54:58	others	others
26048	tacocat-_-tacocat	True	False	False	False	990.0	1770.0	2016-11-18 16:28:40	others	others

	author	n_contributions
2	-banned-	39
210	sweetestdeth	30
186	paperbackgarbage	17
137	col-fancypants	13
120	a_satanic_mechanic	10
154	foul_dwimmerlaik	10
179	mentor13	10
133	cchrist4545	9
26	ClementineCarson	9
124	barlow_straker	8

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
16046	paperbackgarbage	True	False	False	False	199220.0	3282.0	2014-11-12 23:37:57	others	others
16442	col-fancypants	True	True	False	False	290619.0	16547.0	2014-12-16 21:35:57	others	others
24581	sweetestdeth	True	False	False	False	33784.0	39792.0	2016-08-21 19:54:58	others	others